CN112008726B - Composite finite time control method based on exoskeleton robot actuator - Google Patents

Composite finite time control method based on exoskeleton robot actuator Download PDF

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CN112008726B
CN112008726B CN202010889837.1A CN202010889837A CN112008726B CN 112008726 B CN112008726 B CN 112008726B CN 202010889837 A CN202010889837 A CN 202010889837A CN 112008726 B CN112008726 B CN 112008726B
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孙振兴
朱静豪
张兴华
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Zhejiang Xieli Robot Technology Co ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
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Abstract

The invention discloses a composite finite time control method based on an exoskeleton robot actuator, and belongs to the field of exoskeleton robot systems. Aiming at the problems of complex control scheme, low precision and poor robustness and anti-interference capability in the prior art, the invention provides a composite finite time control method based on an exoskeleton robot actuator, which comprises the following steps: constructing a high-order sliding mode disturbance observer for estimating the state and disturbance of a tracking error system, bringing an estimation result into a tracking error, and then bringing the tracking error into a performance index; constructing a lower triangular nonlinear system finite time controller; constructing a state space model of the actuator; and designing a robust finite time control law by utilizing a composite finite time controller and combining a state space model. According to the method, semi-global control rather than global control is adopted to improve the engineering applicability, the control gain can be realized according to a pole configuration mode, the control speed is improved, and the robustness is enhanced.

Description

Composite finite time control method based on exoskeleton robot actuator
Technical Field
The invention relates to the field of robot control systems, in particular to a composite finite time control method based on an exoskeleton robot actuator.
Background
The exoskeleton robot technology is a comprehensive technology which integrates sensing, control, information, fusion and mobile computing and provides a wearable mechanical mechanism for a person as an operator. The present document briefly introduces the development status and trend of exoskeleton world robot technology in the military field. The robot is sleeved outside a human body and is also called a wearable robot. The safety and flexibility of the existing control method need to be improved, and the parameters of the exoskeleton robot are difficult to accurately obtain due to the complexity of mechanical structures, such as nonlinear friction force, clearance and the complexity of a robot actuator. In addition, the dynamic characteristics of subjects vary according to their physiological conditions. The current control methods are not adaptive in the presence of dynamic and motion uncertainties and unknown disturbances of the system.
The Chinese patent application, application No. CN202010132049.8, published as 2020 and 6/16/discloses a self-adaptive compliance control method for an exoskeleton robot for upper limb rehabilitation, wherein the control algorithm consists of two parts: the first part is an admittance control module which is arranged as a control outer ring and can establish a dynamic relation between interaction force between a patient and the exoskeleton and a rehabilitation training track regulating variable, so that the patient can remold a rehabilitation training track according to own active intention; the second part is an adaptive sliding mode control module which is arranged as a control inner ring and used for realizing accurate tracking control of the expected training track and the position adjustment quantity, and the control precision and the system stability are partially dependent on inner ring position control. The method has the disadvantages that the model predictive control of the invention is difficult to process the problems of model uncertainty and interference when the physical control system is processed, and a large amount of calculation is required, which is not beneficial to the realization of the method.
The invention provides a multi-joint combined control system and a method for an exoskeleton robot, which are applied for Chinese patent application, application number CN202010093076.9, and published on 2020, 6, 12.A control system inputs real-time feedback signals of a full sole pressure sensing system and a limb posture sensing system into a multi-signal fusion and decoupling model, completes fusion and decoupling of various signals by the model, outputs various joint motor control variables and controls the operation of a motor; building a multi-signal fusion and decoupling model by using a neural network, and generating a mature application model with multi-signal fusion and decoupling through a large amount of training; the control quantity of various joint motors output by the model is corrected in real time according to a human-computer interaction sensing system in the control system, so that the auxiliary optimization effect is achieved, and the optimal wearing effect of the exoskeleton robot is achieved; in the aspect of joint motor control, the motor is controlled quickly and accurately by real-time current closed-loop control and position (joint angle) closed-loop control of the motor. The method has the disadvantages of more parameters, large calculation amount and complex algorithm realization.
Disclosure of Invention
1. Technical problem to be solved
Aiming at the problems of complex control scheme, low precision and poor robustness and anti-interference capability of the exoskeleton robot in the prior art, the invention provides a finite time control method based on an exoskeleton robot actuator, which adopts semi-global rather than global control to improve the engineering applicability, can realize control gain according to a pole configuration mode, improves the control speed and enhances the robustness.
2. Technical scheme
A composite finite time control method based on exoskeleton robot actuators, comprising the following steps:
step 1, constructing a high-order sliding mode disturbance observer, estimating the state and disturbance of a tracking error system by using the high-order sliding mode disturbance observer, bringing the obtained estimation into a future tracking error, and then bringing the tracking error into a performance index;
step 2, constructing a lower triangular nonlinear system finite time controller based on the observer in the step 1, and constructing a simple finite time controller by partial state vectors and full state vectors of the system and output;
step 3, constructing a state space model of the exoskeleton robot actuator, neglecting interference through analogy of a damped dual-mass system, establishing a nominal mathematical model, and converting the model into a state space form;
and 4, constructing a robust controller with limited time, designing a robust limited time control law by using the composite limited time controller and combining the state space model in the step 3, and thus realizing accurate position control.
Further, in the step 1, a high-order sliding mode disturbance observer of a mechanical arm motion system based on the exoskeleton robot is as follows:
Figure GDA0003120657920000021
wherein:
Figure GDA0003120657920000031
in the formula v1(t),v2(t),v3(t),v4(t),v5(t),v6(t) is the adjustable observer gain,
Figure GDA0003120657920000032
is an estimated value generated by a high-order sliding mode disturbance observer,
Figure GDA0003120657920000033
is the disturbance measured by an observer, λ1,λ2,λ3,λ4,λ5,λ6And L is an adjustable parameter.
Further, in step 2, the lower triangular nonlinear system finite time controller may take the following form after being compensated:
Figure GDA0003120657920000034
wherein
Figure GDA0003120657920000035
Are the partial state vector and the full state vector of the system; y is the system output; phi is ai(·)，i∈N1:4Is a known smooth non-linear function, and the output reference signal is yrY (t) and its nth derivative.
Further, constructing a finite time controller comprises the steps of:
step 201, firstly defining an auxiliary variable vector
Figure GDA0003120657920000036
Figure GDA0003120657920000037
In
Figure GDA0003120657920000038
Determined by the steady state generator given below:
Figure GDA0003120657920000041
step 202, let z ═ col (z)1,z2,z3,z4) Wherein
Figure GDA0003120657920000042
Figure GDA0003120657920000043
Wherein
Figure GDA0003120657920000048
Is a bandwidth factor. Without recursive stability analysis, a simple finite time controller could be explicitly pre-configured in the form:
Figure GDA0003120657920000044
wherein is defined
Figure GDA0003120657920000045
K＝[k1,k2,k3,k4]Is the coefficient vector p(s) s of the Helverz polynomial4+k4s3+k3s2+k2s+k1，r＝(1,1+τ,1+2τ,1+3τ)，
Figure GDA0003120657920000046
Further, in step 3, the method for constructing the state space model of the exoskeleton robot actuator comprises the following steps:
step 301, a motor is coupled with a ball screw at a joint through a high-rigidity torsion spring, two incremental encoders are used for measuring angular displacement of a motor shaft and the ball screw, and a nominal mathematical model in the following form is established by analogy of a damped dual-mass system and ignoring inevitable unmodeled interference:
Figure GDA0003120657920000047
wherein m ismIs the moment of inertia of the motor, mlIs the moment of inertia of the connecting rod, bmIs the viscous friction coefficient of the motor, blIs the viscous friction coefficient of the connecting rod, qmIs the angle of rotation of the motor, qlIs the rotation angle of the connecting rod, k is the stiffness coefficient of the cascade elastic driver, FmIs the motor torque.
Step 302, converting the nominal mathematical model established in step 1 into a state space form, and setting
Figure GDA0003120657920000051
In equation (6), the nominal model is then transformed into the following state space form:
Figure GDA0003120657920000052
further, in step 4, the method for constructing the robust finite time controller includes the following steps:
by giving
Figure GDA0003120657920000053
The following is calculated for tracking the reference quantity in a state space form in formula (7):
Figure GDA0003120657920000054
Figure GDA0003120657920000055
Figure GDA0003120657920000056
substituting the above calculated quantities into (5) can construct the following complex finite time control law applicable to exoskeleton robot actuators:
Figure GDA0003120657920000057
wherein K is [ K ]1,k2,k3,k4]Is a coefficient vector of a helvetz polynomial,
Figure GDA0003120657920000058
Figure GDA0003120657920000059
wherein
Figure GDA00031206579200000511
Is a bandwidth factor that is a function of,
Figure GDA00031206579200000510
is a disturbance measured by an observer, FmIs the motor torque.
3. Advantageous effects
Compared with the prior art, the invention has the advantages that:
the invention designs a continuous time model prediction control system method based on an exoskeleton robot, and by designing a model prediction control method with a nonlinear disturbance observer, optimal offset-free tracking can be realized under various disturbances. Compared with the traditional model prediction control law, the method has better steady-state performance under the condition of time-varying disturbance; meanwhile, the method provides a new performance index, namely the influence of the control input weight on the stability of the closed loop is definitely analyzed.
Drawings
FIG. 1 is a functional block diagram of the present invention;
FIG. 2 is a schematic view of an exoskeleton robot actuator;
fig. 3 is a schematic diagram of the tracking performance of the actuator based on the present invention when τ is 0;
FIG. 4 is a schematic diagram of the tracking performance of an actuator based on the present invention when τ is-0.05;
FIG. 5 is a schematic diagram of the tracking performance of an actuator based on the present invention when τ is-0.1;
fig. 6 is a schematic diagram showing the tracking performance of the actuator based on the present invention when τ is-0.15.
Detailed Description
The invention is described in detail below with reference to the drawings and specific examples.
Example 1
The appearance of the exoskeleton robot actuator is shown in fig. 2, the exoskeleton robot actuator integrally serves as a connecting rod and comprises two motors, and based on the exoskeleton robot actuator, the invention provides a composite finite time control method based on the exoskeleton robot actuator, which comprises the following steps:
step 1, constructing a high-order sliding mode disturbance observer, estimating the state and disturbance of a tracking error system by using the obtained observer, bringing the obtained estimation into a future tracking error, and then bringing the obtained tracking error into a performance index;
as shown in fig. 1, the estimated value of the higher order sliding mode disturbance observer is expressed as:
Figure GDA0003120657920000061
in the above formula:
Figure GDA0003120657920000071
in the formula (2), v1(t),v2(t),v3(t),v4(t),v5(t),v6(t) is the adjustable observer gain,
Figure GDA0003120657920000072
is an estimated value generated by a high-order sliding mode disturbance observer,
Figure GDA0003120657920000073
is the disturbance measured by an observer, λ1,λ2,λ3,λ4,λ5,λ6And L is an adjustable parameter.
Step 2, constructing a lower triangular nonlinear system finite time controller based on the observer in the step 1, and constructing a simple finite time controller by partial state vectors and full state vectors of the system and output;
as shown in fig. 1, the lower triangular nonlinear system finite time controller may take the following form after compensation:
Figure GDA0003120657920000074
in the formula (3)
Figure GDA0003120657920000075
Are the partial state vector and the full state vector of the system; y is the system output; phi is ai(·)，i∈N1:4Is a known smooth non-linear function, and the output reference signal is yrY (t) and its nth derivative.
Specifically, constructing a simple finite time controller includes the following steps:
step 201, firstly defining an auxiliary variable vector
Figure GDA0003120657920000076
Figure GDA0003120657920000077
Wherein
Figure GDA0003120657920000078
Determined by the steady state generator given below:
Figure GDA0003120657920000081
step 202, let z ═ col (z)1,z2,z3,z4) Wherein
Figure GDA0003120657920000082
Figure GDA0003120657920000083
Wherein
Figure GDA0003120657920000088
Is a bandwidth factor.
As shown in fig. 1, without recursive stability analysis, a simple finite time controller can be explicitly pre-configured in the form:
Figure GDA0003120657920000084
wherein is defined
Figure GDA0003120657920000085
K＝[k1,k2,k3,k4]Is the coefficient vector p(s) s of the Helverz polynomial4+k4s3+k3s2+k2s+k1，r＝(1,1+τ,1+2τ,1+3τ)，
Figure GDA0003120657920000086
Step 3, constructing a state space model of the exoskeleton robot actuator, neglecting interference through analogy of a damped dual-mass system, establishing a nominal mathematical model, and converting the nominal mathematical model into a state space form, specifically, the method comprises the following steps:
step 301, as shown in fig. 2, a motor is coupled with a ball screw at a joint through a high-stiffness torsion spring, angular displacements of a motor shaft and the ball screw are measured through two incremental encoders, inevitable unmodeled interference is ignored through analogy of a damped dual-mass system, and a nominal mathematical model in the following form is established:
Figure GDA0003120657920000087
m in formula (6)mIs the moment of inertia of the motor, mlIs the moment of inertia of the connecting rod, bmIs the viscous friction coefficient of the motor, blIs the viscous friction coefficient of the connecting rod, qmIs the angle of rotation of the motor, qlIs the rotation angle of the connecting rod, k is the stiffness coefficient of the cascade elastic driver, FmIs the motor torque.
Step 302, converting the nominal mathematical model established in step 301 into a state space form: is provided with
Figure GDA0003120657920000091
In the formula (6), the nominal model can be transformed into the following state space form
Figure GDA0003120657920000092
Step 4, constructing a finite time robust controller, designing a robust finite time control law by utilizing the composite finite time controller in the step 2 and combining the state space model in the step 3, and further realizing accurate position control;
first pass through given
Figure GDA0003120657920000093
Substituting the tracking reference quantity into the state space form in (7) to calculate:
Figure GDA0003120657920000094
Figure GDA0003120657920000095
Figure GDA0003120657920000096
substituting the above calculated quantities into (5) can construct the following complex finite time control law applicable to the exoskeleton robot actuator:
Figure GDA0003120657920000097
fig. 3 to 6 show that simulation software is used to simulate the exoskeleton robot trajectory tracking graph based on the control method of the present invention, and K ═ 0.5,0.01,0.1,0.01 are respectively simulated]，
Figure GDA0003120657920000098
Time of day, trajectory tracking performance under finite time controllers of different uniformity τ. The right side picture shows the progressive tracking performance of the state feedback controller, and compared with the original track represented by the black dotted line in the left side picture, it can be seen that when τ is a negative value, the control performance is obviously improved, and by comprehensively comparing fig. 3 to fig. 6, it can be seen that the smaller τ is, the faster the convergence speed is, and the smaller the steady-state error is.
The invention and its embodiments have been described above schematically, without limitation, and the invention can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The representation in the drawings is only one of the embodiments of the invention, the actual construction is not limited thereto, and any reference signs in the claims shall not limit the claims concerned. Therefore, if a person skilled in the art receives the teachings of the present invention, without inventive design, a similar structure and an embodiment to the above technical solution should be covered by the protection scope of the present patent. Furthermore, the word "comprising" does not exclude other elements or steps, and the word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. Several of the elements recited in the product claims may also be implemented by one element in software or hardware. The terms first, second, etc. are used to denote names, but not any particular order.

Claims (5)

1. A composite finite time control method based on exoskeleton robot actuators, comprising the steps of:
step 1, constructing a high-order sliding mode disturbance observer for estimating the state and disturbance of a tracking error system, bringing the obtained estimation into a future tracking error, and then bringing the tracking error into a performance index;
step 2, constructing a lower triangular nonlinear system finite time controller based on the observer in the step 1;
step 3, constructing a state space model of the exoskeleton robot actuator, establishing a nominal mathematical model after neglecting interference through analogy of a damped dual-mass system, and converting the mathematical model into a state space form;
step 4, constructing a finite time robust controller, and designing a robust finite time control law by using the composite finite time controller in the step 2 and combining the state space model in the step 3; in the step 1, the constructed high-order sliding mode disturbance observer is as follows:
Figure FDA0003145134620000011
Figure FDA0003145134620000012
Figure FDA0003145134620000013
Figure FDA0003145134620000014
Figure FDA0003145134620000015
Figure FDA0003145134620000016
wherein:
Figure FDA0003145134620000017
Figure FDA0003145134620000018
Figure FDA0003145134620000019
Figure FDA00031451346200000110
Figure FDA00031451346200000111
Figure FDA00031451346200000112
in the formula v1(t),v2(t),v3(t),v4(t),v5(t),v6(t) is the adjustable observer gain,
Figure FDA00031451346200000113
is an estimated value generated by a high-order sliding mode disturbance observer,
Figure FDA00031451346200000114
is the disturbance measured by an observer, λ1,λ2,λ3,λ4,λ5,λ6And L is an adjustable parameter.
2. A method for compound finite time control based on exoskeleton robot actuators as claimed in claim 1 wherein in step 2, the lower triangular nonlinear system finite time controller takes the form of:
Figure FDA0003145134620000021
wherein
Figure FDA0003145134620000022
Is the partial state vector and the full state vector of the system, y is the system output, phii(·)，i∈N1:4Is a known smooth non-linear function, and the output reference signal is yrY (t) and its nth derivative.
3. A method for compound finite time control based on exoskeleton robot actuators as claimed in claim 2 wherein the method of constructing the finite time controller includes the steps of:
step 201, firstly defining an auxiliary variable vector
Figure FDA0003145134620000023
Figure FDA0003145134620000024
In
Figure FDA0003145134620000028
Determined by the steady state generator given below:
Figure FDA0003145134620000025
step 202, let z ═ col (z)1,z2,z3,z4) Wherein
Figure FDA0003145134620000026
Figure FDA0003145134620000027
Wherein
Figure FDA0003145134620000029
Is a bandwidth factor;
without recursive stability analysis, the finite time controller, after compensation, can be explicitly pre-configured in the form:
Figure FDA0003145134620000031
wherein is defined
Figure FDA0003145134620000032
K＝[k1,k2,k3,k4]Is a coefficient vector of a Helvzier polynomial, p(s) ═ s4+k4s3+k3s2+k2s+k1，r＝(1,1+τ,1+2τ,1+3τ)，
Figure FDA0003145134620000033
4. A method for compound finite time control based on exoskeleton robot actuators as claimed in claim 3 wherein in step 3 the method of establishing a state space model of the exoskeleton robot actuators comprises:
step 301, a motor is coupled with a ball screw at a joint through a high-rigidity torsion spring, two incremental encoders are used for measuring angular displacement of a motor shaft and the ball screw, and a nominal mathematical model in the following form is established by analogy of a damped dual-mass system and ignoring inevitable unmodeled interference:
Figure FDA0003145134620000034
wherein m ismIs the moment of inertia of the motor, mlIs the moment of inertia of the connecting rod, bmIs the viscous friction coefficient of the motor, blIs the viscous friction coefficient of the connecting rod, qmIs the angle of rotation of the motor, qlIs the rotation angle of the connecting rod, k is the stiffness coefficient of the cascade elastic driver, FmIs the motor torque;
step 302, converting the nominal mathematical model established in step 1 into a state space form, and setting
Figure FDA0003145134620000035
In equation (6), the nominal model is then transformed into the following state space form:
Figure FDA0003145134620000036
5. a method for composite finite time control based on exoskeleton robot actuators as claimed in claim 4 wherein in step 4, the method for constructing a robust finite time controller is as follows:
given a
Figure FDA0003145134620000041
For tracking the reference quantity and substituting it into the state space form in equation (7):
Figure FDA0003145134620000042
Figure FDA0003145134620000043
Figure FDA0003145134620000044
substituting equation (8) into equation (5) may construct the following complex finite time control law applicable to exoskeleton robot actuators:
Figure FDA0003145134620000045
wherein K is [ K ]1,k2,k3,k4]Is a coefficient vector of a helvetz polynomial,
Figure FDA0003145134620000046
Figure FDA0003145134620000047
wherein
Figure FDA0003145134620000049
Is a bandwidth factor that is a function of,
Figure FDA0003145134620000048
is a disturbance measured by an observer, FmIs the motor torque.
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CN112947123B (en) * 2021-03-29 2022-12-09 南京工业大学 Exoskeleton robot tracking control method and system for inhibiting multi-source interference
CN113721459A (en) * 2021-07-12 2021-11-30 洛阳尚奇机器人科技有限公司 Position control method for two-mass-spring-damping system

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7190141B1 (en) * 2006-01-27 2007-03-13 Villanova University Exoskeletal device for rehabilitation
CN104201941A (en) * 2014-06-30 2014-12-10 浙江工业大学 Permanent magnet synchronous motor chaos control method based on nonlinear expanded state observer
CN109927032A (en) * 2019-03-28 2019-06-25 东南大学 A kind of mechanical arm Trajectory Tracking Control method based on High-Order Sliding Mode observer
CN110327187A (en) * 2019-07-10 2019-10-15 河北工业大学 A kind of band priori torque non-model control method of ectoskeleton
CN111290273A (en) * 2020-02-18 2020-06-16 湖州和力机器人智能科技有限公司 Position tracking optimization control method based on exoskeleton robot flexible actuator

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7190141B1 (en) * 2006-01-27 2007-03-13 Villanova University Exoskeletal device for rehabilitation
CN104201941A (en) * 2014-06-30 2014-12-10 浙江工业大学 Permanent magnet synchronous motor chaos control method based on nonlinear expanded state observer
CN109927032A (en) * 2019-03-28 2019-06-25 东南大学 A kind of mechanical arm Trajectory Tracking Control method based on High-Order Sliding Mode observer
CN110327187A (en) * 2019-07-10 2019-10-15 河北工业大学 A kind of band priori torque non-model control method of ectoskeleton
CN111290273A (en) * 2020-02-18 2020-06-16 湖州和力机器人智能科技有限公司 Position tracking optimization control method based on exoskeleton robot flexible actuator

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Multivariable Finite-Time Control of 5 DOF Upper-Limb Exoskeleton Based on Linear Extended Observer;Gaowei Zhang .et;《IEEE Access》;20180806;全文 *
Robust nonlinear control schemes for finite-time tracking objective of a 5-DOF robotic exoskeleton;AbooeeAli;《INTERNATIONAL JOURNAL OF CONTROL》;20190902(第92卷第9期);第2178-2193页 *
带干扰观测器的机器人有限时间稳定性控制;刘海涛;《机械设计与制造》;20140730;全文 *

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