WO2023010811A1

WO2023010811A1 - Robot control method, apparatus and device based on frictional force

Info

Publication number: WO2023010811A1
Application number: PCT/CN2022/070908
Authority: WO
Inventors: 丁宁; 郝万鈞; 张爱东
Original assignee: 香港中文大学（深圳）
Priority date: 2021-08-03
Filing date: 2022-01-10
Publication date: 2023-02-09
Also published as: CN113510693A; CN113510693B

Abstract

A robot control method, apparatus and device based on a frictional force, and a computer-readable storage medium. The method comprises: by means of taking an electrical parameter of a joint electric motor of a target robot and a structural parameter of a target robot joint as a basis in advance, indirectly establishing a frictional force identification model of a motion parameter and a frictional force of the joint electric motor; during actual control, acquiring a real-time motion parameter of the joint electric motor, and substituting same into the frictional force identification model; and after real-time frictional force data is obtained, obtaining actual force control data for the joint electric motor by means of performing calculation on the basis of the real-time frictional force data and target force control data for the joint electric motor, thereby controlling the joint electric motor according to the actual force control data. Therefore, by means of the robot control method based on a frictional force provided in the present application, robot joint control based on a frictional force can be realized without additionally mounting a force/torque sensor, and the method has the beneficial effects of a high control precision and low costs.

Description

一种基于摩擦力的机器人控制方法、装置及设备A friction-based robot control method, device and equipment

本申请要求于2021年8月3日提交中国专利局、申请号为202110885508.4、发明名称为“一种基于摩擦力的机器人控制方法、装置及设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。This application claims the priority of the Chinese patent application submitted to the China Patent Office on August 3, 2021 with the application number 202110885508.4 and the title of the invention as "a friction-based robot control method, device and equipment", the entire content of which is passed References are incorporated in this application.

技术领域technical field

本申请涉及机器人控制技术领域，特别是涉及一种基于摩擦力的机器人控制方法、装置、设备及计算机可读存储介质。The present application relates to the technical field of robot control, in particular to a friction-based robot control method, device, equipment, and computer-readable storage medium.

背景技术Background technique

图1为一种绳驱关节机器人驱动部分的结构示意图；图2为图1所示绳驱关节机器人驱动部分的正视图；图3为图1所示绳驱关节机器人驱动部分的侧视图；图4为图1所示绳驱关节机器人驱动部分的另一角度结构示意图；图5为本申请实施例提供的一种绳驱关节机器人驱动部分的连接示意图。如图1-4所示，绳驱关节机器人的驱动部分主要由关节电机101、驱动器102、减速器103、绳索绞盘104、编码器107等机构件组成。如图5所示，控制器105接收传感器106获得的机器人的状态量，并根据控制模型控制驱动器102驱动电机101，电机101带动减速器103进而带动绳索以控制机器人关节运动。Fig. 1 is a structural schematic diagram of the driving part of a rope-driven joint robot; Fig. 2 is a front view of the driving part of the rope-driven joint robot shown in Fig. 1; Fig. 3 is a side view of the driving part of the rope-driven joint robot shown in Fig. 1; Fig. 4 is another perspective structural diagram of the driving part of the rope-driven joint robot shown in FIG. 1; FIG. 5 is a schematic connection diagram of the driving part of a rope-driven joint robot provided by the embodiment of the present application. As shown in Figures 1-4, the driving part of the rope-driven joint robot is mainly composed of joint motors 101, drivers 102, reducers 103, rope winches 104, encoders 107 and other mechanical components. As shown in Fig. 5, the controller 105 receives the state quantity of the robot obtained by the sensor 106, and controls the driver 102 to drive the motor 101 according to the control model, and the motor 101 drives the reducer 103 and then drives the rope to control the joint movement of the robot.

在力交互的场景中，机器人需要获取精确的力、速度以及位置控制，基于伺服电机驱动的旋转关节传动***中，不可避免的存在摩擦，摩擦的存在是***低速运行速度产生波动的重要原因，在闭环跟踪低速运动目标和精确定位时产生滞滑、爬行以及极限环等有害特性。In the scene of force interaction, the robot needs to obtain precise force, speed and position control. In the rotary joint transmission system driven by the servo motor, there is inevitably friction. The existence of friction is an important reason for the fluctuation of the system's low-speed operation speed. Harmful characteristics such as stagnation, crawling and limit loops are generated when the closed-loop tracking low-speed moving target and precise positioning are performed.

目前还未有对绳驱关节机器人所提出的基于摩擦力的控制方案。而在其他电机控制方案中，通常通过加装力传感器及力矩传感器的方式来获取力矩，继而基于辨识动力学模型参数理论确定摩擦力并进行补偿。At present, there is no friction-based control scheme proposed for the rope-driven joint robot. In other motor control schemes, the torque is usually obtained by adding a force sensor and a torque sensor, and then the friction force is determined and compensated based on the theory of identifying dynamic model parameters.

然而，这种加装力/力矩传感器的方式增加了结构复杂度并导致较高成本，不具备良好的经济性和通用性。However, this way of adding a force/torque sensor increases the structural complexity and leads to higher costs, and does not have good economy and versatility.

发明内容Contents of the invention

本申请的目的是提供一种基于摩擦力的机器人控制方法、装置、设备及计算机可读存储介质，用于在无需加装力/力矩传感器的前提下实现摩擦力辨识并基于摩擦力对机器人进行关节控制，兼具高控制精度和低成本的有益效果。The purpose of this application is to provide a friction-based robot control method, device, device, and computer-readable storage medium, which are used to realize friction identification and control the robot based on friction without installing a force/torque sensor. Joint control, with the beneficial effects of high control precision and low cost.

为解决上述技术问题，本申请提供一种基于摩擦力的机器人控制方法，包括：In order to solve the above technical problems, the present application provides a friction-based robot control method, including:

预先基于目标机器人的关节电机的电参数和所述目标机器人关节的结构参数，建立所述关节电机的运动参数与摩擦力的摩擦力辨识模型；Based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot in advance, a friction force identification model of motion parameters and friction of the joint motors is established;

获取所述关节电机的实时运动参数；Obtaining real-time motion parameters of the joint motor;

将所述实时运动参数代入所述摩擦力辨识模型，得到实时摩擦力数据；Substituting the real-time motion parameters into the friction identification model to obtain real-time friction data;

根据所述实时摩擦力数据和对所述关节电机的力控制目标数据，计算得到对所述关节电机的实际力控制数据；calculating and obtaining actual force control data for the joint motor according to the real-time friction data and the force control target data for the joint motor;

根据所述实际力控制数据对所述关节电机进行控制。The joint motor is controlled according to the actual force control data.

可选的，所述基于目标机器人的关节电机的电参数和所述目标机器人关节的结构参数，建立所述关节电机的运动参数与摩擦力的摩擦力辨识模型，具体包括：Optionally, based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot, a friction force identification model for motion parameters and friction of the joint motors is established, specifically including:

获取所述关节电机的电机扭矩常数；Obtain the motor torque constant of the joint motor;

对所述关节电机进行速度控制，得到电机转速集合和对应的电机驱动电流集合；performing speed control on the joint motors to obtain a set of motor speeds and a corresponding set of motor drive currents;

将所述电机驱动电流集合与所述电机扭矩常数相乘，得到电机驱动扭矩值集合；multiplying the motor drive current set by the motor torque constant to obtain a motor drive torque value set;

将所述电机转速集合代入基于稳态摩擦力模型的辨识方程，得到理论摩擦扭矩值集合；Substituting the set of motor speeds into an identification equation based on a steady-state friction model to obtain a set of theoretical friction torque values;

以最小化所述理论摩擦扭矩值集合和所述电机驱动扭矩值集合的差值绝对值为目标，求得所述关节电机的第一摩擦力辨识参数；Aiming at minimizing the absolute value of the difference between the set of theoretical friction torque values and the set of motor driving torque values, the first friction force identification parameter of the joint motor is obtained;

将所述第一摩擦力辨识参数代入所述基于稳态摩擦力模型的辨识方程，得到所述摩擦力辨识模型。Substituting the first friction force identification parameters into the identification equation based on the steady-state friction force model to obtain the friction force identification model.

可选的，所述稳态摩擦力模型具体为：Optionally, the steady-state friction model is specifically:

其中，M _f为辨识摩擦力，M _C为库仑摩擦力，M _S为静摩擦力，ω为所述关节电机的实时转速，ω _s为所述关节电机的临界转速，σ _2，θ1为刚性系数，σ _2，θ2为阻尼系数。 Among them, M _f is the identification friction force, M _C is the Coulomb friction force, M _S is the static friction force, ω is the real-time speed of the joint motor, ω _s is the critical speed of the joint motor, σ _{2, θ 1} are stiffness coefficients , σ _{2, θ2} are damping coefficients.

根据所述电机扭矩常数建立所述关节电机的关节转动动力学模型；Establishing a joint rotation dynamics model of the joint motor according to the motor torque constant;

对所述关节电机进行逆M序列的位置控制，采集电机转速信息和电流信息，得到电机转速序列和对应的电机电流序列；performing inverse M-sequence position control on the joint motor, collecting motor speed information and current information, and obtaining a motor speed sequence and a corresponding motor current sequence;

基于所述电机转速序列和所述电机电流序列拟合得到所述关机电机的第二摩擦力辨识参数；Obtaining the second friction force identification parameter of the shutdown motor based on the motor speed sequence and the motor current sequence fitting;

根据所述第二摩擦力辨识参数确定所述关节电机的转动惯量和所述关节电机的等效阻尼系数；determining the moment of inertia of the joint motor and the equivalent damping coefficient of the joint motor according to the second friction force identification parameter;

将所述转动惯量和所述等效阻尼系数代入所述关节转动动力学模型得到所述摩擦力辨识模型。Substituting the moment of inertia and the equivalent damping coefficient into the joint rotation dynamics model to obtain the friction identification model.

可选的，所述摩擦力辨识模型具体为：Optionally, the friction identification model is specifically:

其中，τ _f为辨识摩擦力，τ _c为所述关节电机的最大静摩擦力，ω为所述关节电机的实时转速，B为所述等效阻尼系数。 Wherein, τ _f is the identification friction force, τ _c is the maximum static friction force of the joint motor, ω is the real-time rotational speed of the joint motor, and B is the equivalent damping coefficient.

可选的，所述实时运动参数具体包括：所述关节电机的实时转速、所述关节电机的实时转速加速度和所述关节电机的实时位置；Optionally, the real-time motion parameters specifically include: the real-time rotational speed of the joint motor, the real-time rotational speed acceleration of the joint motor, and the real-time position of the joint motor;

所述根据所述实时摩擦力数据和对所述关节电机的力控制目标数据，计算得到对所述关节电机的实际力控制数据，具体包括：The calculation of the actual force control data for the joint motor based on the real-time friction data and the force control target data for the joint motor specifically includes:

根据所述实时摩擦力数据生成摩擦力补偿力；generating a friction compensation force according to the real-time friction data;

将所述关节电机的转速控制目标减去所述实时转速的差值与预设的虚拟阻尼系数相乘，得到第一补偿力；multiplying the difference between the rotational speed control target of the joint motor and the real-time rotational speed by a preset virtual damping coefficient to obtain a first compensation force;

将所述关节电机的加速度控制目标减去所述实时转速加速度的差值与预设的虚拟摩擦力系数相乘，得到第二补偿力；multiplying the difference between the acceleration control target of the joint motor minus the real-time rotational speed acceleration by a preset virtual friction coefficient to obtain a second compensation force;

将所述关节电机的位置控制目标减去所述实时位置的差值与预设的虚拟刚度系数相乘，得到第三补偿力；multiplying the difference between the position control target of the joint motor and the real-time position by a preset virtual stiffness coefficient to obtain a third compensation force;

以所述关节电机的力控制目标、所述摩擦力补偿力、所述第一补偿力、所述第二补偿力和所述第三补偿力之和为所述关节电机的实际力控制值。The sum of the force control target of the joint motor, the friction compensation force, the first compensation force, the second compensation force and the third compensation force is the actual force control value of the joint motor.

可选的，还包括：Optionally, also include:

获取所述关节电机的工况模型；Obtain the working condition model of the joint motor;

根据所述工况模型生成所述实时转速、所述实时转速加速度、所述实时位置和所述力控制目标。The real-time rotational speed, the real-time rotational speed acceleration, the real-time position and the force control target are generated according to the working condition model.

为解决上述技术问题，本申请还提供一种基于摩擦力的机器人控制装置，包括：In order to solve the above technical problems, the present application also provides a friction-based robot control device, including:

摩擦力辨识单元，用于预先基于目标机器人的关节电机的电参数和所述目标机器人关节的结构参数，建立所述关节电机的运动参数与摩擦力的摩擦力辨识模型；The friction identification unit is used to establish a friction identification model of the motion parameters and friction of the joint motor based on the electrical parameters of the joint motor of the target robot and the structural parameters of the joint of the target robot in advance;

第一获取单元，用于获取所述关节电机的实时运动参数；a first acquisition unit, configured to acquire real-time motion parameters of the joint motor;

第一计算单元，用于将所述实时运动参数代入所述摩擦力辨识模型，得到实时摩擦力数据；a first computing unit, configured to substitute the real-time motion parameters into the friction identification model to obtain real-time friction data;

第二计算单元，用于根据所述实时摩擦力数据和对所述关节电机的力控制目标数据，计算得到对所述关节电机的实际力控制数据；A second computing unit, configured to calculate actual force control data for the joint motor according to the real-time friction data and force control target data for the joint motor;

控制单元，用于根据所述实际力控制数据对所述关节电机进行控制。A control unit, configured to control the joint motors according to the actual force control data.

为解决上述技术问题，本申请还提供一种基于摩擦力的机器人控制设备，包括：In order to solve the above technical problems, the present application also provides a friction-based robot control device, including:

存储器，用于存储指令，所述指令包括上述任意一项所述基于摩擦力的机器人控制方法的步骤；A memory for storing instructions, the instructions including the steps of any one of the friction-based robot control methods described above;

处理器，用于执行所述指令。a processor for executing the instructions.

为解决上述技术问题，本申请还提供一种计算机可读存储介质，其上存储有计算机程序，所述计算机程序被处理器执行时实现如上述任意一项所述基于摩擦力的机器人控制方法的步骤。In order to solve the above-mentioned technical problems, the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the friction-based robot control method as described in any one of the above-mentioned methods is realized. step.

本申请所提供的基于摩擦力的机器人控制方法，通过预先基于目标机器人的关节电机的电参数和目标机器人关节的结构参数，间接地建立关节电机的运动参数与摩擦力的摩擦力辨识模型，在实际控制过程中，获取关节电机的实时运动参数代入摩擦力辨识模型，得到实时摩擦力数据后，根据实时摩擦力数据和对关节电机的力控制目标数据，计算得到对关节电机的实际力控制数据，从而根据实际力控制数据对关节电机进行控制。因此，本申请提供的基于摩擦力的机器人控制方法无需加装力/力矩传感器即可实现基于摩擦力的机器人关节控制，兼具高控制精度和低成本的有益效果。The friction-based robot control method provided by the present application indirectly establishes a friction identification model of joint motor motion parameters and friction force based on the electrical parameters of the joint motor of the target robot and the structural parameters of the target robot joint in advance. In the actual control process, the real-time motion parameters of the joint motor are obtained and substituted into the friction identification model. After the real-time friction data is obtained, the actual force control data of the joint motor is calculated according to the real-time friction data and the force control target data of the joint motor. , so as to control the joint motor according to the actual force control data. Therefore, the friction-based robot control method provided in the present application can realize the friction-based robot joint control without adding force/torque sensors, and has the beneficial effects of high control accuracy and low cost.

本申请还提供一种基于摩擦力的机器人控制装置、设备及计算机可读存储介质，具有上述有益效果，在此不再赘述。The present application also provides a friction-based robot control device, equipment, and computer-readable storage medium, which have the above-mentioned beneficial effects, and will not be repeated here.

附图说明Description of drawings

为了更清楚的说明本申请实施例或现有技术的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单的介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the accompanying drawings that need to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings in the following description are only For some embodiments of the present application, those of ordinary skill in the art can also obtain other drawings based on these drawings without creative effort.

图1为一种绳驱关节机器人驱动部分的结构示意图；Fig. 1 is a structural schematic diagram of the driving part of a rope-driven joint robot;

图2为图1所示绳驱关节机器人驱动部分的正视图；Fig. 2 is the front view of the driving part of the rope-driven joint robot shown in Fig. 1;

图3为图1所示绳驱关节机器人驱动部分的侧视图；Fig. 3 is a side view of the driving part of the rope-driven joint robot shown in Fig. 1;

图4为图1所示绳驱关节机器人驱动部分的另一角度结构示意图；Fig. 4 is a structural schematic diagram of another angle of the driving part of the rope-driven joint robot shown in Fig. 1;

图5为本申请实施例提供的一种绳驱关节机器人驱动部分的连接示意图；Fig. 5 is a schematic diagram of the connection of the driving part of a rope-driven joint robot provided in the embodiment of the present application;

图6为本申请实施例提供的一种基于摩擦力的机器人控制方法的流程图；FIG. 6 is a flow chart of a friction-based robot control method provided in an embodiment of the present application;

图7为本申请实施例提供的一种观测电流示意图；FIG. 7 is a schematic diagram of an observed current provided by an embodiment of the present application;

图8为本申请实施例提供的一种电机扭矩常数标定***的结构示意图；FIG. 8 is a schematic structural diagram of a motor torque constant calibration system provided by an embodiment of the present application;

图9为本申请实施例提供的一种电机扭矩常数标定***的连接示意图；FIG. 9 is a schematic connection diagram of a motor torque constant calibration system provided by an embodiment of the present application;

图10为本申请实施例提供的一种图6中步骤S601的具体实施方式的流程图；FIG. 10 is a flowchart of a specific implementation of step S601 in FIG. 6 provided by the embodiment of the present application;

图11为本申请实施例提供的一种电流环控制器的控制框图；FIG. 11 is a control block diagram of a current loop controller provided in an embodiment of the present application;

图12为本申请实施例提供的一种基于摩擦力前馈的阻抗控制器的控制框图；FIG. 12 is a control block diagram of an impedance controller based on friction feedforward provided by an embodiment of the present application;

图13为本申请实施例提供的一种基于摩擦力的机器人控制装置的结构示意图；Fig. 13 is a schematic structural diagram of a friction-based robot control device provided in an embodiment of the present application;

图14为本申请实施例提供的一种基于摩擦力的机器人控制设备的结构示意图；FIG. 14 is a schematic structural diagram of a friction-based robot control device provided in an embodiment of the present application;

其中，101为关节电机，102为驱动器，103为减速器，104为绳索绞盘，105为控制器，106为传感器，107为编码器，801为测试台架，802为磁滞制动器，803为动态扭矩转速传感器，804为联轴器，805为数据采集卡，806为电流控制器，807为电机驱动器。Among them, 101 is the joint motor, 102 is the driver, 103 is the reducer, 104 is the rope winch, 105 is the controller, 106 is the sensor, 107 is the encoder, 801 is the test bench, 802 is the hysteresis brake, 803 is the dynamic Torque speed sensor, 804 is a shaft coupling, 805 is a data acquisition card, 806 is a current controller, and 807 is a motor driver.

具体实施方式Detailed ways

本申请的核心是提供一种基于摩擦力的机器人控制方法、装置、设备及计算机可读存储介质，用于在无需加装力/力矩传感器的前提下实现摩擦力辨识并基于摩擦力对机器人进行力控制，兼具高控制精度和低成本的有益效果。The core of this application is to provide a friction-based robot control method, device, device, and computer-readable storage medium, which are used to realize friction identification and control the robot based on friction without installing a force/torque sensor. Force control, with the beneficial effects of high control precision and low cost.

下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

图6为本申请实施例提供的一种基于摩擦力的机器人控制方法的流程图。FIG. 6 is a flow chart of a friction-based robot control method provided by an embodiment of the present application.

如图6所示，本申请实施例提供的基于摩擦力的机器人控制方法包括：As shown in Figure 6, the friction-based robot control method provided by the embodiment of the present application includes:

S601：预先基于目标机器人的关节电机的电参数和目标机器人关节的结构参数，建立关节电机的运动参数与摩擦力的摩擦力辨识模型。S601: Based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot in advance, establish a friction force identification model of motion parameters and friction forces of the joint motors.

S602：获取关节电机的实时运动参数。S602: Obtain real-time motion parameters of the joint motor.

S603：将实时运动参数代入摩擦力辨识模型，得到实时摩擦力数据。S603: Substituting the real-time motion parameters into the friction identification model to obtain real-time friction data.

S604：根据实时摩擦力数据和对关节电机的力控制目标数据，计算得到对关节电机的实际力控制数据。S604: According to the real-time friction data and the force control target data on the joint motor, calculate and obtain the actual force control data on the joint motor.

S605：根据实际力控制数据对关节电机进行控制。S605: Control the joint motors according to the actual force control data.

在具体实施中，对步骤S601来说，为实现对关节电机的控制，需要对关节电机的电参数及关节的结构参数进行辨识。辨识方法可以采用测量法或理论辨识法。理论辨识法通过分析机器人模型获取动力学参数，但是分析过程较为复杂。测量法则可以通过测试仪器精准测量电机在不同工况下的稳态及动态特性提取参数，结合辨识的电机与传动参数，进一步辨识关节的摩擦力模型以及相应的动力学参数，配合摩擦模型补偿的控制器从而实现电机的三环控制，由于其成本低，实现方便，精度高，其实现及推广意义较强。故在本申请实施例中，优选采用测量法进行参数辨识。In a specific implementation, for step S601, in order to realize the control of the joint motor, it is necessary to identify the electrical parameters of the joint motor and the structural parameters of the joint. The identification method can use measurement method or theoretical identification method. Theoretical identification method obtains the dynamic parameters by analyzing the robot model, but the analysis process is relatively complicated. The measurement rule can accurately measure the steady-state and dynamic characteristics of the motor under different working conditions through the test instrument to extract parameters, combine the identified motor and transmission parameters, further identify the friction model of the joint and the corresponding dynamic parameters, and cooperate with the friction model compensation The controller thus realizes the three-loop control of the motor. Because of its low cost, convenient realization, and high precision, its realization and promotion significance is strong. Therefore, in the embodiment of the present application, it is preferable to use a measurement method for parameter identification.

针对现有技术中选用电机时电机参数少、无法获知的问题，本申请实施例预先对关节电机的电参数进行辨识，不仅可以解决前述问题，还能够为后续电机控制环节提供参考依据。针对三相无刷电机，电参数辨识主要涉及到电机的相电阻的辨识、相电感的辨识和反应电动势的辨识。针对目标机器人关节的结构参数辨识主要包括对电机扭矩常数、关节转动惯量、等效阻尼系数和关节(包括电机+减速器组合)的摩擦力参数辨识。In view of the problem in the prior art that the motor parameters are few and cannot be known when the motor is selected, the embodiment of the present application identifies the electrical parameters of the joint motor in advance, which can not only solve the aforementioned problem, but also provide a reference for the subsequent motor control link. For three-phase brushless motors, the identification of electrical parameters mainly involves the identification of phase resistance, phase inductance and reaction electromotive force of the motor. The identification of the structural parameters of the target robot joints mainly includes the identification of the motor torque constant, the moment of inertia of the joint, the equivalent damping coefficient and the friction parameter of the joint (including the motor + reducer combination).

基于辨识得到的关节电机的电参数和目标机器人关节的结构参数，建立关节电机的运动参数与摩擦力的摩擦力辨识模型，以实现无需力/力矩传感器来获取外力的情况下计算关节实时的摩擦力。Based on the electrical parameters of the joint motors obtained through identification and the structural parameters of the target robot joints, a friction identification model for the motion parameters and friction of the joint motors is established to realize the real-time friction calculation of the joints without the need for force/torque sensors to obtain external forces force.

则在实际控制过程中，通过采集关节电机的实时运动参数，即可通过摩擦力辨识模型求得实时摩擦力数据，继而根据实时摩擦力数据对关节电机的力控制目标数据进行摩擦损耗的补偿，得到对关节电机的实际力控制数据，并根据实际力控制数据对关节电机进行控制，以确保关节电机达到期望的力控制目标。In the actual control process, by collecting the real-time motion parameters of the joint motor, the real-time friction data can be obtained through the friction identification model, and then the friction loss is compensated for the force control target data of the joint motor according to the real-time friction data. The actual force control data of the joint motor is obtained, and the joint motor is controlled according to the actual force control data, so as to ensure that the joint motor achieves the desired force control target.

本申请实施例提供的基于摩擦力的机器人控制方法，通过预先基于目标机器人的关节电机的电参数和目标机器人关节的结构参数，间接地建立关节电机的运动参数与摩擦力的摩擦力辨识模型，在实际控制过程中，获取关节电机的实时运动参数代入摩擦力辨识模型，得到实时摩擦力数据后，根据实时摩擦力数据和对关节电机的力控制目标数据，计算得到对关节电机的实际力控制数据，从而根据实际力控制数据对关节电机进行控制。因此，本申请实施例提供的基于摩擦力的机器人控制方法无需加装力/力矩传感器即可实现基于摩擦力的机器人关节控制，兼具高控制精度和低成本的有益效果。The friction-based robot control method provided in the embodiment of the present application indirectly establishes a friction force identification model for the motion parameters of the joint motor and the friction force based on the electrical parameters of the joint motor of the target robot and the structural parameters of the joint of the target robot in advance, In the actual control process, the real-time motion parameters of the joint motor are obtained and substituted into the friction identification model. After obtaining the real-time friction data, the actual force control of the joint motor is calculated according to the real-time friction data and the force control target data of the joint motor. Data, so as to control the joint motor according to the actual force control data. Therefore, the friction-based robot control method provided by the embodiment of the present application can realize the friction-based robot joint control without installing a force/torque sensor, and has the beneficial effects of high control accuracy and low cost.

实施例二Embodiment two

图7为本申请实施例提供的一种观测电流示意图；图8为本申请实施例提供的一种电机扭矩常数标定***的结构示意图；图9为本申请实施例提供的一种电机扭矩常数标定***的连接示意图。Figure 7 is a schematic diagram of an observed current provided by the embodiment of the present application; Figure 8 is a schematic structural diagram of a motor torque constant calibration system provided by the embodiment of the present application; Figure 9 is a schematic diagram of a motor torque constant calibration provided by the embodiment of the present application System connection diagram.

在上述实施例的基础上，本申请实施例提供一种对关节电机的电参数和目标机器人关节的结构参数进行测量和辨识的具体实施方式。需要说明的是，在实际应用中，针对不同类型的电机和机器人应用场合，并不限于本申请实施例中所提供的辨识方法。On the basis of the above-mentioned embodiments, the embodiment of the present application provides a specific implementation manner of measuring and identifying the electrical parameters of the joint motor and the structural parameters of the target robot joint. It should be noted that in practical applications, different types of motors and robot applications are not limited to the identification methods provided in the embodiments of the present application.

测量相电阻R _S的具体方式可以为采用万用表进行线电阻的测量后，再进行相电阻R _S的辨识。设无刷电机的三相为U，V，W相(对应的相电阻为R _U、R _V、R _W)，分别测定三相线电阻R _VW、R _UW、R _UV。测量时，保持电机的转子静止不动，对于三组端电阻每一组测定多次(如三次)后取算术平均值为端电阻的值，分别得到R _VW、R _UW、R _UV。 The specific method of measuring the phase resistance R _S may be to use a multimeter to measure the line resistance, and then identify the phase resistance R _S. Let the three phases of the brushless motor be U, V, and W phases (the corresponding phase resistances are R _U , R _V , R _W ), and measure the three-phase line resistances R _VW , R _UW , and R _UV . During the measurement, keep the rotor of the motor stationary, measure each of the three sets of terminal resistances several times (for example, three times), and then take the arithmetic mean value as the value of the terminal resistance, and obtain R _VW , R _UW , and R _UV respectively.

则对于星形接法：Then for star connection:

R _U＝R _med-R _VW； R _U =R _med -R _VW ;

R _V＝R _med-R _UW； R _V =R _med -R _UW ;

R _W＝R _med-R _UV。 R _W =R _med -R _UV .

对于三角形接法：For delta connections:

其中，

in,

测量相电感L _S的具体方式可以为利用示波器，通过在电机三线施加阶跃式电压对电机进行激励，通过观测电流的响应，从而对相电感L _S进行辨识。设无刷电机的额定输入电压为U，在无刷电机的三相为U，V，W分三次实验，分别对三线施加为U _UV＝U、U _VW＝U、U _UW＝U的阶跃电压，并通过观测三相的电流响应曲线，从而计算线电感值。测量时，保持电机的转子静止不动。 The specific way to measure the phase inductance L _S can be to use an oscilloscope to excite the motor by applying a step voltage to the three wires of the motor, and to identify the phase inductance L _S by observing the response of the current. Suppose the rated input voltage of the brushless motor is U, and the three phases of the brushless motor are U, V, and W. The experiments are divided into three times, and the steps of U _UV = U, U _VW = U, U _UW = U are applied to the three lines respectively. Voltage, and by observing the current response curve of the three phases, the line inductance value is calculated. During the measurement, keep the rotor of the motor stationary.

则对于星形接法：Then for star connection:

其中，

分别为U _UV、U _VW、U _UW三组电压激励下稳定一定时间(如2分钟)后的电流稳定值。τ _UV、τ _VW、τ _UW对应为

的时刻(从线电压/线电流变化为0的时刻)。观测的电流图如图7所示。 in,

Respectively, U _UV , U _VW , U _UW three sets of current stable values after being stabilized for a certain period of time (such as 2 minutes) under voltage excitation. τ _UV , τ _VW , τ _UW correspond to

The moment (from the moment when the line voltage/line current changes to 0). The observed current diagram is shown in Figure 7.

对电机的反应电动势K _e进行辨识，完成对关节电气动态响应模型的辨识。具体地，将电机固定到台架上，通过联轴器同轴连接到对拖旋转电机上，并通过位置控制器对拖旋转电机进行一圈的驱动，通过示波器测量待测电机的两线电压，示波器上连续出现对应波形，测试得到波形波峰数为N，则极对数

使用速度控制器控制对拖电机，设待测电机的额定转速为N _rated，将额定转速均分(例如可以均分为20份)后得到

按照转速递变的方式对电机峰值线电压进行测定，得到对应转速

下的线电压波峰值的算数平均值及对应的频率

则

取多组

(如20组)算数平均值得到

记为关节电机的反应电动势K _e。 The reaction electromotive force K _e of the motor is identified to complete the identification of the electrical dynamic response model of the joint. Specifically, fix the motor on the stand, connect it coaxially to the towed rotating motor through a coupling, and drive the towed rotating motor for one revolution through the position controller, and measure the two-wire voltage of the motor to be tested with an oscilloscope , the corresponding waveform appears continuously on the oscilloscope, and the number of waveform peaks obtained from the test is N, then the number of pole pairs

Use the speed controller to control the dragging motor, set the rated speed of the motor to be tested as N _rated , and divide the rated speed evenly (for example, it can be divided into 20 parts) to get

Measure the peak line voltage of the motor according to the speed change method to obtain the corresponding speed

The arithmetic mean value of the peak value of the line voltage wave and the corresponding frequency

but

Take multiple groups

(such as 20 groups) the arithmetic mean is obtained

Record it as the reaction electromotive force K _e of the joint motor.

针对目标机器人关节的结构参数辨识主要包括对电机扭矩常数、关节转动惯量、等效阻尼系数和关节(包括电机+减速器组合)的摩擦力参数辨识。为解决由于传动形式复杂导致的转动惯量以及摩擦系数复杂难以辨识问题、为后期设计高动态的控制器作为重要参数参考，本申请实施例提供如下电机机械参数辨识方法。The identification of the structural parameters of the target robot joints mainly includes the identification of the motor torque constant, the moment of inertia of the joint, the equivalent damping coefficient and the friction parameter of the joint (including the motor + reducer combination). In order to solve the problem of difficult identification of the moment of inertia and friction coefficient due to the complex transmission form, and to use the high dynamic controller as an important parameter reference for later design, the embodiment of the present application provides the following motor mechanical parameter identification method.

标定电机扭矩常数K _T可以利用如图8-9所示的电机扭矩常数标定***实现。利用测试台架801固定关节电机101，利用磁滞制动器802锁住电机轴，以电流控制方式，以不同的电流集合

驱动电机101，记录串联的动态转速扭矩传感器803的信息，辨识出电机扭矩常数K _T。具体测量步骤包括： Calibrating the motor torque constant K _T can be realized by using the motor torque constant calibration system shown in Fig. 8-9. Use the test bench 801 to fix the joint motor 101, use the hysteresis brake 802 to lock the motor shaft, and use the current control method to gather different currents

Drive the motor 101, record the information of the dynamic rotational speed torque sensor 803 connected in series, and identify the motor torque constant K _T . The specific measurement steps include:

将关节电机101固定到测试台架801上，通过联轴器804连接到动态扭矩转速传感器803上，通过数据采集卡805采集磁滞制动器802的数据并输入到电流控制器806；并通过磁滞制动器802进行锁定。The joint motor 101 is fixed on the test bench 801, connected to the dynamic torque speed sensor 803 through the coupling 804, and the data of the hysteresis brake 802 is collected by the data acquisition card 805 and input to the current controller 806; and through the hysteresis The brake 802 is locked.

使用关节电机801的电流控制器806通过电机驱动器807对关节电机801进行控制，设定关节电机801的额定电流为I _rated，将额定电流I _rated均分(例如可以均分为20份)后得到

按照电流递变的方式对电机801进行测定得到对应的扭矩

以(I _i，τ _i)为坐标点进行拟合，得到

记为关节电机801的电机扭矩常数。 Use the current controller 806 of the joint motor 801 to control the joint motor 801 through the motor driver 807, set the rated current of the joint motor 801 as I _rated , and divide the rated current I _rated evenly (for example, it can be divided into 20 parts) to obtain

Measure the motor 801 according to the way of current gradient to obtain the corresponding torque

Taking (I _i , τ _i ) as the coordinate point for fitting, we get

Denote as the motor torque constant of the joint motor 801 .

针对关节转动惯量J _J可以采用对关节进行逆M序列的位置控制，通过采集电流以及转速信息，利用多组参数批处理，从而辨识关机整体的转动惯量J _J和等效阻尼系数B。具体的，关节转动动力学模型如下： For the moment of inertia J _J of the joint, the inverse M-sequence position control of the joint can be adopted. By collecting the current and speed information, and using multiple sets of parameter batch processing, the overall moment of inertia J _J and the equivalent damping coefficient B of the shutdown can be identified. Specifically, the joint rotation dynamics model is as follows:

J _J·ω＝K _T·I-τ _f， (1) J _J ·ω=K _T ·I-τ _f , (1)

其中，ω为关节电机的实时转速，K _T为电机扭矩常数，I为电机电流，τ _f为静摩擦力，τ _c为关节电机的最大静摩擦力，B为等效阻尼系数。 Among them, ω is the real-time rotational speed of the joint motor, K _T is the motor torque constant, I is the motor current, τ _f is the static friction force, τ _c is the maximum static friction force of the joint motor, and B is the equivalent damping coefficient.

公式(1)、(2)中的待辨识参数包括关节电机运动的正反两方向的简化摩擦力参数

以及关节转动惯量J _J。 The parameters to be identified in formulas (1) and (2) include the simplified friction parameters of the positive and negative directions of joint motor movement

and joint moment of inertia J _J .

为求解公式(1)、(2)，首先将机器人关节固定在检测装置上，使用位置控制器对关节电机进行驱动，以逆M序列的位置指令，该位置指令的幅值为A≥10°对关节电机进行驱动，振幅为2mm，对关节电机进行位置和速度的采集，使用零阶保持器对关节电机的转速以及电流进行采样，采样时间为

得到N≥10000个采样点。设： In order to solve formulas (1) and (2), first fix the joints of the robot on the detection device, use the position controller to drive the joint motors, and reverse the position command of the M sequence, the amplitude of the position command is A≥10° Drive the joint motor with an amplitude of 2mm, collect the position and speed of the joint motor, use the zero-order holder to sample the speed and current of the joint motor, and the sampling time is

Get N≥10000 sampling points. set up:

其中，W和W ₁为转速序列，I ₁为电流序列。基于最小二乘法，设： Among them, W and _W1 are the rotation speed sequence, and _I1 is the current sequence. Based on the least squares method, let:

从而以最小化E为目标，进行参数向量辨识。设：Therefore, with the goal of minimizing E, the parameter vector identification is carried out. set up:

则待辨识的参数向量为：Then the parameter vector to be identified is:

其中，K _θd、T _θs、p _θs、λ(k)、Φ为过程参数，具体可以以最小化E为目标，通过遗传算法得到辨识参数向量。从而可以得到如下结果： Among them, K _θd , T _θs , p _θs , λ(k), and Φ are process parameters. Specifically, the identification parameter vector can be obtained by genetic algorithm with the goal of minimizing E. Thus the following results can be obtained:

通过本申请实施例提供的辨识方法，能够准确获知关节电机相关的电参数和结构参数，为实现精准的力控奠定了基础。Through the identification method provided by the embodiment of the present application, the electrical parameters and structural parameters related to the joint motor can be accurately known, which lays a foundation for realizing precise force control.

实施例三Embodiment three

图10为本申请实施例提供的一种图6中步骤S601的具体实施方式的流程图。FIG. 10 is a flow chart of a specific implementation of step S601 in FIG. 6 provided by an embodiment of the present application.

除了上述电参数和结构参数的辨识外，还需进行关节(关节电机和减速器组合)的摩擦力参数辨识，为进一步辨识关节的转动惯量作为重要的摩擦力模型参考。In addition to the identification of the electrical parameters and structural parameters mentioned above, it is also necessary to identify the friction parameters of the joint (combination of joint motor and reducer), which serves as an important friction model reference for further identification of the moment of inertia of the joint.

具体地，如图10所示，步骤S601中基于目标机器人的关节电机的电参数和目标机器人关节的结构参数，建立关节电机的运动参数与摩擦力的摩擦力辨识模型，具体可以包括：Specifically, as shown in FIG. 10 , in step S601, based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot, a friction force identification model for motion parameters and friction of the joint motors is established, which may specifically include:

S1001：获取关节电机的电机扭矩常数。S1001: Obtain the motor torque constant of the joint motor.

S1002：对关节电机进行速度控制，得到电机转速集合和对应的电机驱动电流集合。S1002: Perform speed control on the joint motors to obtain a set of motor speeds and a corresponding set of motor drive currents.

S1003：将电机驱动电流集合与电机扭矩常数相乘，得到电机驱动扭矩值集合。S1003: Multiply the motor drive current set by the motor torque constant to obtain a motor drive torque value set.

S1004：将电机转速集合代入基于稳态摩擦力模型的辨识方程，得到理论摩擦扭矩值集合。S1004: Substitute the set of motor speed into the identification equation based on the steady-state friction model to obtain a set of theoretical friction torque values.

S1005：以最小化理论摩擦扭矩值集合和电机驱动扭矩值集合的差值绝对值为目标，求得关节电机的第一摩擦力辨识参数。S1005: Aiming at minimizing the absolute value of the difference between the theoretical friction torque value set and the motor driving torque value set, obtain the first friction force identification parameter of the joint motor.

S1006：将第一摩擦力辨识参数代入基于稳态摩擦力模型的辨识方程，得到摩擦力辨识模型。S1006: Substituting the first friction force identification parameter into an identification equation based on a steady-state friction force model to obtain a friction force identification model.

其中，电机扭矩常数K _T可以通过上述步骤获取。 Wherein, the motor torque constant K _T can be obtained through the above steps.

对于步骤S1002和步骤S1003来说，对关节电机进行速度控制，通过不同的电机转速集合

采集到用于驱动关节电机的对应的电流集合

相乘得到对应的电机驱动扭矩值集合： For step S1002 and step S1003, the speed control of the joint motor is carried out through different motor speed sets

Collect the corresponding current set used to drive the joint motor

Multiply to get the corresponding set of motor drive torque values:

对于步骤S1004来说，稳态摩擦力模型可以选用Stribeck摩擦力模型。但是，Stribeck摩擦力模型在高转速下的摩擦力拟合较差。故本申请实施例提供一种优化的稳态摩擦力模型如下：For step S1004, the steady-state friction model may be the Stribeck friction model. However, the friction fit of the Stribeck friction model is poor at high speeds. Therefore, the embodiment of the present application provides an optimized steady-state friction model as follows:

其中，M _f为辨识摩擦力，M _C为库仑摩擦力，M _S为静摩擦力，ω为关节电机的实时转速，ω _s为关节电机的临界转速，σ _2，θ1为刚性系数，σ _2，θ2为阻尼系数。 Among them, M _f is the identification friction force, M _C is the Coulomb friction force, M _S is the static friction force, ω is the real-time speed of the joint motor, ω _s is the critical speed of the joint motor, σ2 _{, θ1} is the stiffness coefficient, σ2 _{, θ2} is the damping coefficient.

由于高转速区间摩擦力随速度上升的斜率是逐渐减小的，采用公式(14)所示的稳态摩擦力模型，可以对斜率减小的现象有很好的拟合作用。Since the slope of the friction force in the high speed range decreases gradually with the increase of the speed, the steady-state friction model shown in formula (14) can have a good fitting effect on the phenomenon of decreasing slope.

记公式(14)中的摩擦力参数为第一摩擦力参数，包括正方向的摩擦力参数

和反方向的摩擦力参数

需要分别对正方向和反方向的摩擦力参数进行辨识，则基于稳态摩擦力模型的辨识方程为： Note that the friction parameter in formula (14) is the first friction parameter, including the friction parameter in the positive direction

and friction parameters in the opposite direction

It is necessary to identify the friction parameters in the positive direction and the reverse direction respectively, then the identification equation based on the steady-state friction model is:

其中，M _f，theo，i为基于摩擦力模型的理论摩擦扭矩值。 Among them, M _{f, theo, i} are the theoretical friction torque values based on the friction model.

将步骤S1002采集到的电机转速集合代入方程(15)后得到集合

After substituting the motor speed set collected in step S1002 into equation (15), the set is obtained

对于步骤S1005来说，设定如下函数：For step S1005, set the following function:

以最小化L(D _i)为目标，得到最佳拟合参数组合： With the goal of minimizing L(D _i ), the best fitting parameter combination is obtained:

对于步骤S1006，将公式(17)、(18)得到的参数代入公式(15)的辨识方程，得到摩擦力辨识模型如下：For step S1006, the parameters obtained by formulas (17) and (18) are substituted into the identification equation of formula (15), and the friction force identification model is obtained as follows:

正方向摩擦力模型具体为：The specific friction model in the positive direction is:

反方向摩擦力模型具体为：The friction model in the opposite direction is specifically:

本申请实施例所提出的优化的摩擦力辨识模型，能够覆盖旋转关节摩擦力的高低速状态时的精确辨识，通过设计辨识模型可以弥补传统的Stribeck摩擦力模型在高速段时斜率变低而精度降低的缺点，从而提升摩擦力的辨识精度，提高力控精度。且对于各类旋转关节的摩擦力辨识均有此有益效果，而不仅仅限于绳驱旋转关节摩擦力的辨识。The optimized friction identification model proposed in the embodiment of the present application can cover the accurate identification of the high and low speed state of the rotary joint friction, and the identification model can be designed to make up for the low slope and accuracy of the traditional Stribeck friction model at high speeds. Reduce the shortcomings, thereby improving the identification accuracy of friction force and improving the force control accuracy. And it has this beneficial effect on the identification of friction force of all kinds of rotary joints, not limited to the identification of friction force of rope-driven rotary joints.

实施例四Embodiment four

本申请实施例三提供了一种优化的稳态摩擦力模型，能够覆盖高速、低速运转的摩擦力辨识精度。而对于力控性能要求不高的场景，为了简化计算，可以选用本申请实施例二给出的关节转动动力学模型来确定摩擦力。则步骤S601中基于目标机器人的关节电机的电参数和目标机器人关节的结构参数，建立关节电机的运动参数与摩擦力的摩擦力辨识模型，具体可以包括：Embodiment 3 of the present application provides an optimized steady-state friction model, which can cover the friction identification accuracy of high-speed and low-speed operation. For the scene where the force control performance is not high, in order to simplify the calculation, the joint rotation dynamic model given in the second embodiment of the present application can be used to determine the friction force. Then in step S601, based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot, a friction force identification model for motion parameters and friction of the joint motors is established, which may specifically include:

获取关节电机的电机扭矩常数；Obtain the motor torque constant of the joint motor;

根据电机扭矩常数建立关节电机的关节转动动力学模型；Establish the joint rotation dynamics model of the joint motor according to the motor torque constant;

对关节电机进行逆M序列的位置控制，采集电机转速信息和电流信息，得到电机转速序列和对应的电机电流序列；Carry out inverse M-sequence position control on the joint motor, collect motor speed information and current information, and obtain the motor speed sequence and the corresponding motor current sequence;

基于电机转速序列和电机电流序列拟合得到关机电机的第二摩擦力辨识参数；Based on the motor speed sequence and the motor current sequence fitting, the second friction force identification parameter of the shutdown motor is obtained;

根据第二摩擦力辨识参数确定关节电机的转动惯量和关节电机的等效阻尼系数；determining the moment of inertia of the joint motor and the equivalent damping coefficient of the joint motor according to the second friction force identification parameter;

将转动惯量和等效阻尼系数代入关节转动动力学模型得到摩擦力辨识模型。The moment of inertia and equivalent damping coefficient are substituted into the dynamic model of joint rotation to obtain the friction identification model.

则摩擦力辨识模型采用公式(2)：

以

为第二摩擦力辨识参数，求解过程可以参考本申请实施例二。 Then the friction identification model adopts the formula (2):

by

It is the second friction force identification parameter, and the solution process can refer to Embodiment 2 of the present application.

应用本申请实施例提供的摩擦力辨识方法，在进行关节转动惯量和等效阻尼系数的辨识的同时即可确定摩擦力辨识模型，达到降低计算复杂度、降低解算延迟的效果。By applying the friction force identification method provided in the embodiment of the present application, the friction force identification model can be determined while identifying the joint moment of inertia and the equivalent damping coefficient, so as to achieve the effects of reducing computational complexity and delay of solution.

实施例五Embodiment five

图11为本申请实施例提供的一种电流环控制器的控制框图；图12为本申请实施例提供的一种基于摩擦力前馈的阻抗控制器的控制框图。FIG. 11 is a control block diagram of a current loop controller provided in an embodiment of the present application; FIG. 12 is a control block diagram of a friction feedforward based impedance controller provided in an embodiment of the present application.

关节电机的力控制的重要环节是电流控制器的设计与调控。在上述实施例的基础上，本申请实施例提供一种电流控制器的设计方案，如图11所示，设计比例积分(PI)控制器，通过本申请实施例二辨识得到的相电阻R _S和相电感L _S，以及电流环的带宽得到比例控制器与积分控制器的参数，完成电流环控制器的设计。 The important part of the force control of the joint motor is the design and regulation of the current controller. On the basis of the above-mentioned embodiments, the embodiment of the present application provides a design scheme of a current controller, as shown in Figure 11, a proportional-integral (PI) controller is designed, and the phase resistance R _S The parameters of the proportional controller and the integral controller are obtained by summing the phase inductance L _S and the bandwidth of the current loop to complete the design of the current loop controller.

其中，i _{q_ref}为q轴电流控制参考值；K _e为本申请实施例二辨识得到的关节电机的反应电动势；G _{C_ctl}(s)为电流的PI控制器，传递函数为

G _{inv_d}(s)为基于SVPWM算法的逆变器，传递函数等效为

G _{s_pmsm}(s)为基于i _d＝0矢量控制策略的电机模型，

G _cf(s)为电流滤波器，其传递函数为

其中ω _cf为滤波器的截止频率。 Wherein, i _{q_ref} is the reference value of the q-axis current control; K _e is the reaction electromotive force of the joint motor identified in Embodiment 2 of the present application; G _{C_ctl} (s) is the PI controller of the current, and the transfer function is

G _{inv_d} (s) is an inverter based on the SVPWM algorithm, and the transfer function is equivalent to

G _{s_pmsm} (s) is the motor model based on _id = 0 vector control strategy,

G _cf (s) is a current filter whose transfer function is

Where ω _cf is the cut-off frequency of the filter.

设计电流环的带宽为：

则电流的PI控制器参数设计为： The bandwidth of the designed current loop is:

Then the PI controller parameters of the current are designed as:

在电流控制器的基础上，进一步设计基于摩擦力前馈的阻抗控制器。如图12所示，根据摩擦力辨识模型为前馈，对关节电机的电流控制器进行控制输入i _{q_ref}。 Based on the current controller, an impedance controller based on friction feedforward is further designed. As shown in FIG. 12 , according to the friction identification model as feedforward, control input i _{q_ref} is made to the current controller of the joint motor.

本申请实施例一提供一种在建立了摩擦力辨识模型后，通过采集关节电机的实时运动参数代入摩擦力辨识模型得到实时摩擦力数据，而后基于摩擦力数据进行关节电机的控制的方案。在实际应用中，采集得到的关节电机的实时运动参数可以仅包括关节电机的实时转速，将关节电机的实时转速代入上述实施例中提供的描述关节电机转速与摩擦力关系的摩擦力辨识模型即可得到摩擦力，从而在关节电机的力控制目标的基础上加上摩擦力得到关节电机的实际力控制值，即可实现对摩擦力的补偿。 Embodiment 1 of the present application provides a scheme in which after the friction identification model is established, the real-time friction data is obtained by collecting the real-time motion parameters of the joint motors and substituting them into the friction identification model, and then the joint motors are controlled based on the friction data. In practical applications, the collected real-time motion parameters of the joint motors may only include the real-time rotational speed of the joint motors, and the real-time rotational speeds of the joint motors are substituted into the friction force identification model describing the relationship between the joint motor speed and the frictional force provided in the above-mentioned embodiments. The friction force can be obtained, so that the actual force control value of the joint motor can be obtained by adding the friction force to the force control target of the joint motor, and the compensation for the friction force can be realized.

而为了适应不同的工况，在本申请实施例中，实时运动参数具体可以包括：关节电机的实时转速、关节电机的实时转速加速度和关节电机的实时位置。In order to adapt to different working conditions, in the embodiment of the present application, the real-time motion parameters may specifically include: the real-time rotational speed of the joint motor, the real-time rotational speed acceleration of the joint motor, and the real-time position of the joint motor.

则步骤S604：根据实时摩擦力数据和对关节电机的力控制目标数据，计算得到对关节电机的实际力控制数据，具体包括：Then step S604: According to the real-time friction force data and the force control target data on the joint motor, calculate the actual force control data on the joint motor, specifically including:

根据实时摩擦力数据生成摩擦力补偿力；Generate friction compensation force based on real-time friction data;

将关节电机的转速控制目标减去实时转速的差值与预设的虚拟阻尼系数相乘，得到第一补偿力；Multiply the difference between the speed control target of the joint motor minus the real-time speed and the preset virtual damping coefficient to obtain the first compensation force;

将关节电机的加速度控制目标减去实时转速加速度的差值与预设的虚拟摩擦力系数相乘，得到第二补偿力；Multiply the difference between the acceleration control target of the joint motor minus the real-time speed acceleration and the preset virtual friction coefficient to obtain the second compensation force;

将关节电机的位置控制目标减去实时位置的差值与预设的虚拟刚度系数相乘，得到第三补偿力；Multiply the difference between the position control target of the joint motor minus the real-time position and the preset virtual stiffness coefficient to obtain the third compensation force;

以关节电机的力控制目标、摩擦力补偿力、第一补偿力、第二补偿力和第三补偿力之和为关节电机的实际力控制值。The actual force control value of the joint motor is taken as the sum of the force control target of the joint motor, the friction compensation force, the first compensation force, the second compensation force and the third compensation force.

在具体实施中，如图12所示，可以在确定关节电机的实时转速ω之后，通过积分计算和微分计算分别得到关节电机的实时位置θ和关节电机的实时转速加速度

实时转速ω的确定方法可以为通过测量仪器实时采集关节电机的转速，也可以如图12所示的以关节电机的转速控制目标

为关节电机的实时转速ω代入摩擦力辨识模型M _f(ω)计算得到辨识摩擦力M _f。 In a specific implementation, as shown in Figure 12, after determining the real-time rotational speed ω of the joint motor, the real-time position θ of the joint motor and the real-time rotational speed acceleration of the joint motor can be respectively obtained through integral calculation and differential calculation

The method of determining the real-time rotation speed ω can be to collect the rotation speed of the joint motor in real time through the measuring instrument, or to control the target with the rotation speed of the joint motor as shown in Figure 12.

The real-time rotational speed ω of the joint motor is substituted into the friction identification model M _f (ω) to calculate the identified friction force M _f .

本申请实施例中加入虚拟阻尼系数B _d、虚拟摩擦力系数M _d和虚拟刚度系数K _d来适应复杂工况下的要求。虚拟阻尼系数B _d、虚拟摩擦力系数 M _d和虚拟刚度系数K _d为模拟的阻抗模型参数，通过调节虚拟阻尼系数B _d、虚拟摩擦力系数M _d和虚拟刚度系数K _d来适应不同工况下的要求。 In the embodiment of the present application, a virtual damping coefficient B _d , a virtual friction coefficient M _d and a virtual stiffness coefficient K _d are added to meet the requirements under complex working conditions. The virtual damping coefficient B _d , virtual friction coefficient M _d and virtual stiffness coefficient K _d are the parameters of the simulated impedance model, which can be adapted to different working conditions by adjusting the virtual damping coefficient B _d , virtual friction coefficient M _d and virtual stiffness coefficient K _d next request.

如图12所示，本申请实施例在阻抗控制器中还加入了工况模型M _L(θ)和位置规划器θ _r(t)(图12中未示出)。其中，工况模型M _L(θ）用于根据当前工况确定关节电机的力控制目标，位置规划器用于根据当前工况确定关节电机的转速控制目标

关节电机的加速度控制目标

关节电机的位置控制目标θ _r。则本申请实施例提供的基于摩擦力的机器人控制方法还包括：获取关节电机的工况模型；根据工况模型生成实时转速、实时转速加速度、实时位置和力控制目标。 As shown in FIG. 12 , the embodiment of the present application also adds a working condition model M _L (θ) and a position planner θ _r (t) to the impedance controller (not shown in FIG. 12 ). Among them, the working condition model M _L (θ) is used to determine the force control target of the joint motor according to the current working condition, and the position planner is used to determine the speed control target of the joint motor according to the current working condition

Acceleration control target of joint motor

The position control target θ _r of the joint motor. Then, the friction-based robot control method provided by the embodiment of the present application further includes: acquiring the working condition model of the joint motor; and generating real-time speed, real-time speed acceleration, real-time position and force control target according to the working condition model.

另外，在未知工况时，可以省去工况模型M _L(θ)，同时调节阻抗控制器参数B _d、M _d、K _d来适应复杂工况要求。 In addition, when the working condition is unknown, the working condition model M _L (θ) can be omitted, and the impedance controller parameters B _d , M _d , and K _d can be adjusted to meet the requirements of complex working conditions.

则基于图12所示控制框图的阻抗控制器F _virtual如下式所示： Then the impedance controller F _virtual based on the control block diagram shown in Figure 12 is shown in the following formula:

则得到的关节电机的实际力控制值F _d如下式所示： Then the actual force control value F _d of the joint motor is obtained as follows:

对于电流控制器的输入i _{q_ref}为： For the input i _{q_ref} of the current controller is:

其中，T _L(θ)为外界需求负载曲线。 Among them, T _L (θ) is the external demand load curve.

基于本申请实施例提供的基于摩擦力前馈的阻抗控制器，对绳驱关节机器人可以根据精准摩擦力以及工况曲线提供的摩擦力前馈以及设计的阻抗参数来动态地调节关节拉绳的力-位特性，既可以实现精准的力控制，又可以实现类似阻抗特性的复杂力-位控制效果。而通过动态调节阻抗控制器参数可以适应不同环境的要求而改变关节的适应性，对关节电机均具有良好的控制效果，适用性强。Based on the impedance controller based on friction feedforward provided by the embodiment of the present application, the rope-driven joint robot can dynamically adjust the joint pull rope according to the friction feedforward provided by the precise friction force and the working condition curve and the designed impedance parameters. The force-position characteristic can not only realize precise force control, but also realize complex force-position control effect similar to impedance characteristic. By dynamically adjusting the parameters of the impedance controller, the adaptability of the joint can be changed to meet the requirements of different environments, and it has a good control effect on the joint motor and has strong applicability.

上文详述了基于摩擦力的机器人控制方法对应的各个实施例，在此基础上，本申请还公开了与上述方法对应的基于摩擦力的机器人控制装置、设备及计算机可读存储介质。Various embodiments corresponding to the friction-based robot control method are described in detail above. On this basis, the application also discloses a friction-based robot control device, equipment, and computer-readable storage medium corresponding to the above method.

实施例六Embodiment six

图13为本申请实施例提供的一种基于摩擦力的机器人控制装置的结构示意图。Fig. 13 is a schematic structural diagram of a friction-based robot control device provided by an embodiment of the present application.

如图13所示，本申请实施例提供的基于摩擦力的机器人控制装置包括：As shown in Figure 13, the friction-based robot control device provided by the embodiment of the present application includes:

摩擦力辨识单元1301，用于预先基于目标机器人的关节电机的电参数和目标机器人关节的结构参数，建立关节电机的运动参数与摩擦力的摩擦力辨识模型；The friction identification unit 1301 is used to establish a friction identification model of motion parameters and friction of the joint motor based on the electrical parameters of the joint motor of the target robot and the structural parameters of the joint of the target robot in advance;

第一获取单元1302，用于获取关节电机的实时运动参数；The first acquisition unit 1302 is configured to acquire real-time motion parameters of the joint motor;

第一计算单元1303，用于将实时运动参数代入摩擦力辨识模型，得到实时摩擦力数据；The first calculation unit 1303 is configured to substitute real-time motion parameters into the friction identification model to obtain real-time friction data;

第二计算单元1304，用于根据实时摩擦力数据和对关节电机的力控制目标数据，计算得到对关节电机的实际力控制数据；The second calculation unit 1304 is used to calculate the actual force control data for the joint motor according to the real-time friction data and the force control target data for the joint motor;

控制单元1305，用于根据实际力控制数据对关节电机进行控制。The control unit 1305 is used to control the joint motors according to the actual force control data.

可选的，本申请实施例提供的基于摩擦力的机器人控制装置还包括：Optionally, the friction-based robot control device provided in the embodiment of the present application further includes:

第二获取单元，用于获取关节电机的工况模型；The second acquisition unit is used to acquire the working condition model of the joint motor;

第三计算单元，用于根据工况模型生成实时转速、实时转速加速度、实时位置和力控制目标。The third calculation unit is used to generate real-time rotational speed, real-time rotational speed acceleration, real-time position and force control target according to the working condition model.

由于装置部分的实施例与方法部分的实施例相互对应，因此装置部分的实施例请参见方法部分的实施例的描述，这里暂不赘述。Since the embodiment of the device part corresponds to the embodiment of the method part, please refer to the description of the embodiment of the method part for the embodiment of the device part, and details will not be repeated here.

实施例七Embodiment seven

图14为本申请实施例提供的一种基于摩擦力的机器人控制设备的结构示意图。FIG. 14 is a schematic structural diagram of a friction-based robot control device provided by an embodiment of the present application.

如图14所示，本申请实施例提供的基于摩擦力的机器人控制设备包括：As shown in Figure 14, the friction-based robot control device provided by the embodiment of the present application includes:

存储器1410，用于存储指令，所述指令包括上述任意一项实施例所述的基于摩擦力的机器人控制方法的步骤；The memory 1410 is used to store instructions, and the instructions include the steps of the friction-based robot control method described in any one of the above-mentioned embodiments;

处理器1420，用于执行所述指令。The processor 1420 is configured to execute the instruction.

其中，处理器1420可以包括一个或多个处理核心，比如3核心处理器、8核心处理器等。处理器1420可以采用数字信号处理DSP(Digital Signal Processing)、现场可编程门阵列FPGA(Field－Programmable Gate Array)、可编程逻辑阵列PLA(Programmable Logic Array)中的至少一种硬件形式来实现。处理器1420也可以包括主处理器和协处理器，主处理器是用于对在唤醒状态下的数据进行处理的处理器，也称中央处理器CPU(Central Processing Unit)；协处理器是用于对在待机状态下的数据进行处理的低功耗处理器。在一些实施例中，处理器1420可以集成有图像处理器GPU(Graphics Processing Unit)，GPU用于负责显示屏所需要显示的内容的渲染和绘制。一些实施例中，处理器1420还可以包括人工智能AI(Artificial Intelligence)处理器，该AI处理器用于处理有关机器学习的计算操作。Wherein, the processor 1420 may include one or more processing cores, such as a 3-core processor, an 8-core processor, and the like. The processor 1420 can be realized by at least one hardware form of digital signal processing DSP (Digital Signal Processing), field programmable gate array FPGA (Field-Programmable Gate Array), and programmable logic array PLA (Programmable Logic Array). The processor 1420 may also include a main processor and a coprocessor, the main processor is a processor for processing data in the wake-up state, and is also called a central processing unit CPU (Central Processing Unit); Low-power processor for processing data in standby state. In some embodiments, the processor 1420 may be integrated with an image processor GPU (Graphics Processing Unit), and the GPU is used for rendering and drawing the content that needs to be displayed on the display screen. In some embodiments, the processor 1420 may also include an artificial intelligence AI (Artificial Intelligence) processor, which is used to process computing operations related to machine learning.

存储器1410可以包括一个或多个计算机可读存储介质，该计算机可读存储介质可以是非暂态的。存储器1410还可包括高速随机存取存储器，以及非易失性存储器，比如一个或多个磁盘存储设备、闪存存储设备。本实施例中，存储器1410至少用于存储以下计算机程序1411，其中，该计算机程序1411被处理器1420加载并执行之后，能够实现前述任一实施例公开的基于摩擦力的机器人控制方法中的相关步骤。另外，存储器1410所存储的资源还可以包括操作***1412和数据1413等，存储方式可以是短暂存储或者永久存储。其中，操作***1412可以为Windows。数据1413可以包括但不限于上述方法所涉及到的数据。Memory 1410 may include one or more computer-readable storage media, which may be non-transitory. The memory 1410 may also include high-speed random access memory, and non-volatile memory, such as one or more magnetic disk storage devices, flash memory storage devices. In this embodiment, the memory 1410 is at least used to store the following computer program 1411, wherein, after the computer program 1411 is loaded and executed by the processor 1420, it can realize the correlation in the friction-based robot control method disclosed in any of the foregoing embodiments. step. In addition, the resources stored in the memory 1410 may also include an operating system 1412 and data 1413, etc., and the storage method may be temporary storage or permanent storage. Wherein, the operating system 1412 may be Windows. The data 1413 may include but not limited to the data involved in the above method.

在一些实施例中，基于摩擦力的机器人控制设备还可包括有显示屏1430、电源1440、通信接口1450、输入输出接口1460、传感器1470以及通信总线1480。In some embodiments, the friction-based robot control device may further include a display screen 1430 , a power supply 1440 , a communication interface 1450 , an input and output interface 1460 , a sensor 1470 and a communication bus 1480 .

本领域技术人员可以理解，图14中示出的结构并不构成对基于摩擦力的机器人控制设备的限定，可以包括比图示更多或更少的组件。Those skilled in the art can understand that the structure shown in Fig. 14 does not constitute a limitation to the friction-based robot control device, and may include more or less components than those shown in the illustration.

本申请实施例提供的基于摩擦力的机器人控制设备，包括存储器和处理器，处理器在执行存储器存储的程序时，能够实现如上所述的基于摩擦力的机器人控制方法，效果同上。The friction-based robot control device provided by the embodiment of the present application includes a memory and a processor. When the processor executes the program stored in the memory, it can implement the friction-based robot control method described above, with the same effect as above.

实施例八Embodiment eight

需要说明的是，以上所描述的装置、设备实施例仅仅是示意性的，例如，模块的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个模块或组件可以结合或者可以集成到另一个***，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或模块的间接耦合或通信连接，可以是电性，机械或其它的形式。作为分离部件说明的模块可以是或者也可以不是物理上分开的，作为模块显示的部件可以是或者也可以不是物理模块，即可以位于一个地方，或者也可以分布到多个网络模块上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。It should be noted that the above-described device and device embodiments are only illustrative. For example, the division of modules is only a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components May be combined or may be integrated into another system, or some features may be omitted, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or modules may be in electrical, mechanical or other forms. A module described as a separate component may or may not be physically separated, and a component shown as a module may or may not be a physical module, that is, it may be located in one place, or may also be distributed to multiple network modules. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

另外，在本申请各个实施例中的各功能模块可以集成在一个处理模块中，也可以是各个模块单独物理存在，也可以两个或两个以上模块集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。In addition, each functional module in each embodiment of the present application may be integrated into one processing module, each module may exist separately physically, or two or more modules may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules.

集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，执行本申请各个实施例所述方法的全部或部分步骤。If the integrated modules are realized in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or part of the contribution to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium , executing all or part of the steps of the methods described in the various embodiments of the present application.

为此，本申请实施例还提供一种计算机可读存储介质，该计算机可读存储介质上存储有计算机程序，计算机程序被处理器执行时实现如基于摩擦力的机器人控制方法的步骤。To this end, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, steps such as a friction-based robot control method are implemented.

该计算机可读存储介质可以包括：U盘、移动硬盘、只读存储器ROM (Read-Only Memory)、随机存取存储器RAM(Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。The computer-readable storage medium may include: U disk, mobile hard disk, read-only memory ROM (Read-Only Memory), random access memory RAM (Random Access Memory), magnetic disk or optical disk and other media that can store program codes .

本实施例中提供的计算机可读存储介质所包含的计算机程序能够在被处理器执行时实现如上所述的基于摩擦力的机器人控制方法的步骤，效果同上。The computer program contained in the computer-readable storage medium provided in this embodiment can realize the steps of the above-mentioned friction-based robot control method when executed by a processor, and the effect is the same as above.

以上对本申请所提供的一种基于摩擦力的机器人控制方法、装置、设备及计算机可读存储介质进行了详细介绍。说明书中各个实施例采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似部分互相参见即可。对于实施例公开的装置、设备及计算机可读存储介质而言，由于其与实施例公开的方法相对应，所以描述的比较简单，相关之处参见方法部分说明即可。应当指出，对于本技术领域的普通技术人员来说，在不脱离本申请原理的前提下，还可以对本申请进行若干改进和修饰，这些改进和修饰也落入本申请权利要求的保护范围内。The friction-based robot control method, device, equipment and computer-readable storage medium provided by the present application have been described in detail above. Each embodiment in the description is described in a progressive manner, each embodiment focuses on the difference from other embodiments, and the same and similar parts of each embodiment can be referred to each other. As for the device, equipment and computer-readable storage medium disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and for relevant details, please refer to the description of the method part. It should be pointed out that those skilled in the art can make some improvements and modifications to the application without departing from the principles of the application, and these improvements and modifications also fall within the protection scope of the claims of the application.

还需要说明的是，在本说明书中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。It should also be noted that in this specification, relative terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that these entities or operations There is no such actual relationship or order between the operations. Furthermore, the term "comprises", "comprises" or any other variation thereof is intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus comprising a set of elements includes not only those elements, but also includes elements not expressly listed. other elements of or also include elements inherent in such a process, method, article, or device. Without further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article or apparatus comprising said element.

Claims

一种基于摩擦力的机器人控制方法，其特征在于，包括：A method for controlling a robot based on friction, comprising:

预先基于目标机器人的关节电机的电参数和所述目标机器人关节的结构参数，建立所述关节电机的运动参数与摩擦力的摩擦力辨识模型；Based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot in advance, a friction force identification model of motion parameters and friction of the joint motors is established;

获取所述关节电机的实时运动参数；Obtaining real-time motion parameters of the joint motor;

将所述实时运动参数代入所述摩擦力辨识模型，得到实时摩擦力数据；Substituting the real-time motion parameters into the friction identification model to obtain real-time friction data;

根据所述实时摩擦力数据和对所述关节电机的力控制目标数据，计算得到对所述关节电机的实际力控制数据；calculating and obtaining actual force control data for the joint motor according to the real-time friction data and the force control target data for the joint motor;

根据所述实际力控制数据对所述关节电机进行控制。The joint motor is controlled according to the actual force control data.
根据权利要求1所述的机器人控制方法，其特征在于，所述基于目标机器人的关节电机的电参数和所述目标机器人关节的结构参数，建立所述关节电机的运动参数与摩擦力的摩擦力辨识模型，具体包括：The robot control method according to claim 1, characterized in that, based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot, the frictional force between the motion parameters of the joint motors and the frictional force is established Identify models, including:

获取所述关节电机的电机扭矩常数；Obtain the motor torque constant of the joint motor;

对所述关节电机进行速度控制，得到电机转速集合和对应的电机驱动电流集合；performing speed control on the joint motors to obtain a set of motor speeds and a corresponding set of motor drive currents;

将所述电机驱动电流集合与所述电机扭矩常数相乘，得到电机驱动扭矩值集合；multiplying the motor drive current set by the motor torque constant to obtain a motor drive torque value set;

将所述电机转速集合代入基于稳态摩擦力模型的辨识方程，得到理论摩擦扭矩值集合；Substituting the set of motor speeds into an identification equation based on a steady-state friction model to obtain a set of theoretical friction torque values;

以最小化所述理论摩擦扭矩值集合和所述电机驱动扭矩值集合的差值绝对值为目标，求得所述关节电机的第一摩擦力辨识参数；Aiming at minimizing the absolute value of the difference between the set of theoretical friction torque values and the set of motor driving torque values, the first friction force identification parameter of the joint motor is obtained;

将所述第一摩擦力辨识参数代入所述基于稳态摩擦力模型的辨识方程，得到所述摩擦力辨识模型。Substituting the first friction force identification parameters into the identification equation based on the steady-state friction force model to obtain the friction force identification model.
根据权利要求2所述的机器人控制方法，其特征在于，所述稳态摩擦力模型具体为：The robot control method according to claim 2, wherein the steady-state friction model is specifically:

其中，M _f为辨识摩擦力，M _C为库仑摩擦力，M _S为静摩擦力，ω为所述关节电机的实时转速，ω _s为所述关节电机的临界转速，σ _2，θ1为刚性系数，σ _2，θ2为阻尼系数。 Among them, M _f is the identification friction force, M _C is the Coulomb friction force, M _S is the static friction force, ω is the real-time speed of the joint motor, ω _s is the critical speed of the joint motor, σ _{2, θ 1} are stiffness coefficients , σ _{2, θ2} are damping coefficients.
根据权利要求1所述的机器人控制方法，其特征在于，所述基于目标机器人的关节电机的电参数和所述目标机器人关节的结构参数，建立所述关节电机的运动参数与摩擦力的摩擦力辨识模型，具体包括：The robot control method according to claim 1, characterized in that, based on the electrical parameters of the joint motors of the target robot and the structural parameters of the joints of the target robot, the frictional force between the motion parameters of the joint motors and the frictional force is established Identify models, including:

获取所述关节电机的电机扭矩常数；Obtain the motor torque constant of the joint motor;

根据所述电机扭矩常数建立所述关节电机的关节转动动力学模型；Establishing a joint rotation dynamics model of the joint motor according to the motor torque constant;

对所述关节电机进行逆M序列的位置控制，采集电机转速信息和电流信息，得到电机转速序列和对应的电机电流序列；performing inverse M-sequence position control on the joint motor, collecting motor speed information and current information, and obtaining a motor speed sequence and a corresponding motor current sequence;

基于所述电机转速序列和所述电机电流序列拟合得到所述关机电机的第二摩擦力辨识参数；Obtaining the second friction force identification parameter of the shutdown motor based on the motor speed sequence and the motor current sequence fitting;

根据所述第二摩擦力辨识参数确定所述关节电机的转动惯量和所述关节电机的等效阻尼系数；determining the moment of inertia of the joint motor and the equivalent damping coefficient of the joint motor according to the second friction force identification parameter;

将所述转动惯量和所述等效阻尼系数代入所述关节转动动力学模型得到所述摩擦力辨识模型。Substituting the moment of inertia and the equivalent damping coefficient into the joint rotation dynamics model to obtain the friction identification model.
根据权利要求4所述的机器人控制方法，其特征在于，所述摩擦力辨识模型具体为：The robot control method according to claim 4, wherein the friction identification model is specifically:

其中，τ _f为辨识摩擦力，τ _c为所述关节电机的最大静摩擦力，ω为所述关节电机的实时转速，B为所述等效阻尼系数。 Wherein, τ _f is the identification friction force, τ _c is the maximum static friction force of the joint motor, ω is the real-time rotational speed of the joint motor, and B is the equivalent damping coefficient.
根据权利要求1所述的机器人控制方法，其特征在于，所述实时运动参数具体包括：所述关节电机的实时转速、所述关节电机的实时转速加速度和所述关节电机的实时位置；The robot control method according to claim 1, wherein the real-time motion parameters specifically include: the real-time rotational speed of the joint motor, the real-time rotational speed acceleration of the joint motor, and the real-time position of the joint motor;

所述根据所述实时摩擦力数据和对所述关节电机的力控制目标数据，计算得到对所述关节电机的实际力控制数据，具体包括：The calculation of the actual force control data for the joint motor based on the real-time friction data and the force control target data for the joint motor specifically includes:

根据所述实时摩擦力数据生成摩擦力补偿力；generating a friction compensation force according to the real-time friction data;

将所述关节电机的转速控制目标减去所述实时转速的差值与预设的虚拟阻尼系数相乘，得到第一补偿力；multiplying the difference between the rotational speed control target of the joint motor and the real-time rotational speed by a preset virtual damping coefficient to obtain a first compensation force;

将所述关节电机的加速度控制目标减去所述实时转速加速度的差值与预设的虚拟摩擦力系数相乘，得到第二补偿力；The difference between the acceleration control target of the joint motor minus the real-time rotational speed acceleration is multiplied by the preset virtual friction coefficient to obtain the second compensation force;

将所述关节电机的位置控制目标减去所述实时位置的差值与预设的虚拟刚度系数相乘，得到第三补偿力；multiplying the difference between the position control target of the joint motor and the real-time position by a preset virtual stiffness coefficient to obtain a third compensation force;

以所述关节电机的力控制目标、所述摩擦力补偿力、所述第一补偿力、所述第二补偿力和所述第三补偿力之和为所述关节电机的实际力控制值。The sum of the force control target of the joint motor, the friction compensation force, the first compensation force, the second compensation force and the third compensation force is the actual force control value of the joint motor.
根据权利要求6所述的机器人控制方法，其特征在于，还包括：The robot control method according to claim 6, further comprising:

获取所述关节电机的工况模型；Obtain the working condition model of the joint motor;

根据所述工况模型生成所述实时转速、所述实时转速加速度、所述实时位置和所述力控制目标。The real-time rotational speed, the real-time rotational speed acceleration, the real-time position and the force control target are generated according to the working condition model.
一种基于摩擦力的机器人控制装置，其特征在于，包括：A robot control device based on friction, characterized in that it comprises:

摩擦力辨识单元，用于预先基于目标机器人的关节电机的电参数和所述目标机器人关节的结构参数，建立所述关节电机的运动参数与摩擦力的摩擦力辨识模型；The friction identification unit is used to establish a friction identification model of the motion parameters and friction of the joint motor based on the electrical parameters of the joint motor of the target robot and the structural parameters of the joint of the target robot in advance;

第一获取单元，用于获取所述关节电机的实时运动参数；a first acquisition unit, configured to acquire real-time motion parameters of the joint motor;

第一计算单元，用于将所述实时运动参数代入所述摩擦力辨识模型，得到实时摩擦力数据；a first computing unit, configured to substitute the real-time motion parameters into the friction identification model to obtain real-time friction data;

第二计算单元，用于根据所述实时摩擦力数据和对所述关节电机的力控制目标数据，计算得到对所述关节电机的实际力控制数据；A second computing unit, configured to calculate actual force control data for the joint motor according to the real-time friction data and force control target data for the joint motor;

控制单元，用于根据所述实际力控制数据对所述关节电机进行控制。A control unit, configured to control the joint motors according to the actual force control data.
一种基于摩擦力的机器人控制设备，其特征在于，包括：A friction-based robot control device, characterized in that it includes:

存储器，用于存储指令，所述指令包括权利要求1至7任意一项所述基于摩擦力的机器人控制方法的步骤；A memory for storing instructions, the instructions including the steps of the friction-based robot control method according to any one of claims 1 to 7;

处理器，用于执行所述指令。a processor for executing the instructions.
一种计算机可读存储介质，其上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现如权利要求1至7任意一项所述基于摩擦力的机器人控制方法的步骤。A computer-readable storage medium, on which a computer program is stored, wherein, when the computer program is executed by a processor, the steps of the friction-based robot control method according to any one of claims 1 to 7 are realized.