CN114310571B - Intelligent control method in robot automatic grinding operation process - Google Patents
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Abstract
The invention relates to an intelligent control method for a robot automatic grinding operation process. The robot is used for fixing a force sensor at the tail end, the tail end of the sensor clamps a workpiece, the workpiece is ground and processed on the abrasive belt machine by utilizing the position control of the robot, and the force sensor is used for detecting the contact force and moment between the workpiece and the abrasive belt machine. And the upper computer, the sensor and the robot are transmitted by using an IP/UDP protocol to realize control. The grinding operation adopts force-position hybrid control to realize high-precision contact force control, realizes a gravity compensation algorithm and solving of contact force, and realizes constant force control based on fuzzy PID control. In order to effectively avoid overgrinding at the position with larger fluctuation of the starting position, the end point and the workpiece surface of the grinding path, moment control is added into a control strategy to realize force and moment fusion control. The intelligent control strategy can realize quantitative removal of materials in workpiece grinding operation, and is high in universality and suitable for grinding of various complex curved surface parts.
Description
Technical Field
The invention relates to the field of intelligent manufacturing and processing, in particular to an intelligent control method in the process of automatically grinding complex curved surfaces by robots.
Background
At present, the processing of complex curved surface parts such as blades mainly relies on manual grinding, so that consistency of processing quality is difficult to ensure, the processing efficiency is low, the processing environment is severe, and the labor intensity is high. In order to obtain higher processing quality and production efficiency, a large number of numerical control devices are designed and successfully applied to processing of parts such as blades, and the numerical control machine tool has the defects of high cost, poor flexibility, long process period and the like. In recent years, with rapid innovation of robotics, robotics have been applied to processes such as handling, assembly, and processing, and have become an important step in the development of the intelligent manufacturing and processing industry. The application of the robot in the grinding process is mature, and the robot grinding system has the advantages of good flexibility, strong universality, low cost and the like. For the robot automatic grinding technology, the contact force control in the grinding operation process is a key link, and the precision of the contact force control is related to the processing quality and the processing efficiency of the surface of the part and is also a necessary condition for quantitatively removing materials. The research on force control at home and abroad mainly comprises passive force control and active force control, wherein the passive force control mainly uses a flexible mechanism which can absorb or store energy and is composed of springs, damping and the like, so that the robot can naturally conform to external acting force when contacting with a working environment, and the passive force control method is difficult to finish the processing of complex curved surfaces such as blades. For main power control, the force control strategy applied to processing and manufacturing at home and abroad mainly comprises an impedance control strategy and a force position hybrid control strategy, and the control algorithm mainly adopts PID control, so that the control algorithm can finish automatic grinding processing of the part robot with simple structure and low precision due to low contact force control precision. For the processing of complex curved surfaces such as blades, the precision requirement is high, the quantitative removal of robot automatic grinding is important, and therefore the control precision requirement on contact force is high. At present, accurate control of contact force is difficult to ensure by some control algorithms at home and abroad, high-precision grinding of complex curved surfaces such as blades cannot be realized, and moment control is not considered by most control algorithms.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a force-position hybrid self-adaptive control method based on fuzzy PID control, which is applied to robot automatic grinding operation to realize high-precision processing of blade complex curved surfaces.
The technical scheme adopted by the invention for achieving the purpose is as follows: an intelligent control method for a robot automatic grinding operation process comprises the following steps:
controlling the tail end of an arm of the robot to move according to the preset track position;
in the moving process, the force sensor is used for detecting the contact force and moment between the workpiece and the grinding machine tool in real time;
solving grinding contact force according to the gravity compensation of the end load of the robot;
according to the gravity compensation result, the automatic grinding force position hybrid control of the robot is realized, so that the actual contact force approaches to the target value to realize the automatic grinding processing of the robot;
meanwhile, moment control is adopted in the automatic grinding process, the position and posture information of the next track of the robot grinding process are calculated, and constant force control and force and moment fusion in the whole process are realized.
The method is realized based on an intelligent control system of the robot automatic grinding operation process, and the system comprises an industrial robot, a force sensor, a grinding workpiece, a grinding machine tool and an upper computer; the robot is characterized in that the force sensor is fixed at the tail end of the robot through a connecting tool, the workpiece is ground and processed through the clamping of the connecting tool at the tail end of the force sensor, an instruction is transmitted between the upper computer and a driver and a sensor of the industrial robot through an IP/UDP protocol, and the upper computer controls the tail end position of an arm of the robot to realize the grinding and processing of the workpiece on a grinding machine tool.
The solving the grinding contact force according to the gravity compensation of the end load of the robot comprises the following steps:
according to the transformation relation of each coordinate system of the robot automatic grinding system, solving the load of a workpiece and other position variables, and performing least square method to complete gravity compensation;
S F＝ S G+ S F zero
wherein ,S f is the contact force data actually detected by the force sensor, S g is the detected effect value of the load gravity in the force sensor coordinate system, S F zero is the zero drift value detected by the force sensor;
the solution of the grinding contact force is that,
wherein ,Fcg Is the contact force to be determined and the contact force is,
is a workpiece seatMapping relation from coordinate system of force sensor, < ->
The transformation relation from the grinding machine coordinate system to the workpiece coordinate system is shown.
The method for realizing the robot automatic grinding force position hybrid control according to the gravity compensation result comprises the following steps: the tail end position of a given robot controls the robot to plan a path X according to a preset track p And (3) walking, wherein the contact force is controlled by adopting force-position mixed control in the process.
The contact force control is as follows:
the contact force control process adjusts the actual contact force F through force-position hybrid control cg Contact force F with target p And correcting the difference value and the planned path in real time to realize the flexible control of the tail end force of the robot.
The contact force control process adopts a contact force control method based on fuzzy PID control;
definition e f Is the target contact force F p With actual contact force F cg Is the difference, ec f Is e f Rate of change, ec f and ef Is the input of the fuzzy PID controller, deltaK p ,ΔK i ,ΔK d Is the proportional, integral and differential regulation parameter of PID controller, and uses fuzzy set e f ,ec f ,ΔK p ,ΔK i ,ΔK d Value of = { NB, NM, NS, ZO, PS, PM, PB }, and final output parameter K of fuzzy PID control is adjusted p 、K i 、K d : thereby realizing the actual contact force F cg Approach target contact force F p 。
Moment control is adopted in the automatic grinding process, and next track position and posture information of the robot grinding process are calculated, and the method comprises the following steps:
when the robot automatic grinding processing is carried out, moment information is detected in real time, and if the moment value exceeds a reference moment value, the terminal gesture of the robot is adjusted to realize constant moment control.
After the technical scheme is adopted, the invention has the following beneficial effects:
1. the gravity compensation technology can rapidly realize load gravity solution, and the contact force in the automatic grinding operation process is calculated according to the compensation result.
2. The intelligent control of the contact force based on the fuzzy PID control can realize the high-precision control of the grinding contact force, and ensure that the contact force is maintained within the allowed range of the set value in the grinding process.
3. And the quantitative removal of the material for workpiece grinding is completed according to the high-precision control of the contact force, so that the efficiency and the precision of robot automation for grinding complex curved surfaces such as blades and the like are realized.
4. The introduction of moment control can effectively avoid over-grinding phenomena of the initial position and the final position of a grinding path and the position with larger fluctuation change of the surface of the workpiece.
5. The control strategy of the invention has strong universality and can be suitable for grinding processing of various parts.
Drawings
Fig. 1 is a relationship between various coordinate systems during robotic automated grinding operations.
Fig. 2 is a diagram of a robotic automated grinding process force-position hybrid control strategy designed in accordance with the present invention.
FIG. 3 shows a fuzzy PID contact force intelligent control strategy according to the present invention.
FIG. 4 is a table of fuzzy rules used in the fuzzy PID control process of the present invention.
FIG. 5 is a block diagram of a torque control method of the present invention.
Fig. 6 shows the information transmission mode and process of the automatic grinding system of the robot.
Wherein 1 is a robot, 2 is a force sensor, 3 is a grinding workpiece, and 4 is a grinding machine tool.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and examples. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be embodied in many other forms than described herein and similarly modified by those skilled in the art without departing from the spirit or scope of the invention, which is therefore not limited to the specific embodiments disclosed below.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
As shown in fig. 1, the gravity compensation and the contact force are solved according to the relation between the coordinate systems. The device for implementing the invention consists of an industrial robot 1, a six-dimensional force sensor 2, a grinding workpiece 3, a grinding machine tool 4 and an upper computer control system 5. The robot tail end is connected with a tool to fix a force sensor, the sensor tail end is connected with the tool to clamp a workpiece, an instruction is transmitted between an upper computer and a driver and a sensor of the industrial robot 1 through an IP/UDP protocol, the upper computer utilizes the position control of the robot to realize the grinding processing of the workpiece on the belt sander, and the force sensor is used for detecting the contact force and moment between the workpiece and the belt sander. The upper computer receives real-time data from the robot and the force sensor, calculates the position (Z-direction value) and the attitude information (A-direction attitude value) of the robot according to an algorithm and transmits the position (Z-direction value) and the attitude information to the robot, so that the constant force control of the whole process is realized. The grinding machine 4 may be a grinding tool such as a belt sander. Relationship between coordinate systems during robotic automated grinding operations, wherein O 0 Representing world coordinates, O 1 Represents a robot base coordinate system, O 6 Represents the robot flange coordinate system, O S Representing the sensor coordinate system, O T Representing the coordinate system of the grinding machine.
Step one: solving for gravity compensation, the specific process can be according to the one shown in figure 1, S f is a value of force and moment read out from the force sensor, and can be expressed as:
S F＝[ s f x s f y s f z s m x s m y s m z ] T
wherein ,s f x s f y s f z s m x s m y s m z the force and moment values of the tail end of the mechanical arm in three directions are respectively read by the sensor;
S F zero is the zero drift value of the force sensor, and can be expressed as:
S F zero ＝[ s f xzero s f yzero s f zzero s m xzero s m yzero s m zzero ] T
wherein ,s f xzero s f yzero s f zzero s m xzero s m yzero s m zzero zero drift values of force and moment in three directions at the tail end of the mechanical arm read by the sensor respectively;
S g is the force of the load gravity in the force sensor coordinate system, and can be expressed as:
wherein 0 g= [0 0-G0 0 0 0] T ，
Is the force sensor coordinate system O S To world coordinate system O 0 Is a transformation matrix of->
Is the world coordinate system O 0 To the robot base coordinate system O 1 Is a transformation matrix of->
Is a robot base coordinate system O 1 To robot flange coordinate system O 6 Is a transformation matrix of->
Is a robot flange coordinate system O 6 To the force sensor coordinate system O S Is used for the transformation matrix of the (a). s k is a load barycenter coordinate correlation matrix, and the coordinates of the load barycenter in the sensor coordinate system can be expressed as (k x ,k y ,k z ) Then s k can be expressed in the sensor coordinate system as:
in summary, all unknown parameters can be solved by using the least squares method according to the following equation.
S F＝ S G+ S F zero
wherein ,S f is the contact force data actually detected by the force sensor, S g is the detected effect value of the load gravity in the force sensor coordinate system, S F zero is the zero drift value detected by the force sensor;
the contact force F of the step 1 cg The calculation of (2) can be derived from the following equation:
wherein Fcg Is the contact force to be determined and the contact force is,
is the transformation relation of the object coordinate system to the force sensor coordinate system, < >>
And the conversion relation between the abrasive belt grinding machine coordinate system and the workpiece coordinate system is shown.
Step two: in the automatic grinding system of the robot, the force and position mixed control is adoptedStrategy control, control process is shown in figure 2, F p and Xp The positions of the target contact force and the track plan, F cg The actual contact force, matrix S, is a force/bit control selection matrix (6X 6 diagonal matrix representing six dimensions X, Y, Z, a, B, C of the robot), element 0 of the matrix diagonal representing the position control, and 1 representing the force control. Position control of path X according to trajectory planning p Controlling the end position of the robot, wherein the contact force control process is based on the converted actual contact force F cg Contact force F with target reference p And correcting the planned path in real time by a force control strategy according to the difference value, so as to realize the flexible control of the tail end force of the robot.
Step three: in the force-bit hybrid control process described in the second step, the contact force control process proposes a contact force intelligent control strategy based on fuzzy PID control, as shown in FIG. 3, e f Is the target contact force F p With actual contact force F cg Is the difference, ec f Is e f Rate of change of (c) at the same time ec f and ef Is the input of the fuzzy PID controller, deltaK p ,ΔK i ,ΔK d Is the proportional, integral and differential adjusting parameter of the PID controller. E, according to the fuzzy PID control theory and the working condition of the robot automatic grinding operation f ,ec f In the range of-6.ltoreq.e f ≤6,-6≤ec f 6. Ltoreq.thus e f ,ec f The basic arguments of (a) are:
e f ＝(-6,-3,-1,0,1,3,6)
ec f ＝(-6,-3,-1,0,1,3,6)
according to the PID control strategy of the robot automatic grinding system, three parameters K of PID are obtained by utilizing a trial-and-error method p 、K i 、K d Is a range of values: k is more than or equal to 0.06 p ≤0.14,0≤K i ≤0.6,0.02≤K d Less than or equal to 0.1, wherein the initial value of the PID parameter is K p0 ＝0.1,K i0 ＝0.03,K d0 =0.06, thus Δk p ,ΔK i ,ΔK d The basic arguments of (a) are:
ΔK p ＝(-0.04,-0.02,-0.01,0,0.01,0.02,0.04)
ΔK i ＝(-0.03,-0.02,-0.01,0,0.01,0.02,0.03)
ΔK d ＝(-0.04,-0.02,-0.01,0,0.01,0.02,0.04)
the final output parameters of the fuzzy PID control are expressed as:
K p ＝K p0 +ΔK p
K i ＝K i0 +ΔK i
K d ＝K d0 +ΔK d
e f ,ec f ,ΔK p ,ΔK i ,ΔK d is defined as the fuzzy set of (a) to (b),
e f ,ec f ,ΔK p ,ΔK i ,ΔK d ＝{NB,NM,NS,ZO,PS,PM,PB}
there are 2 basic principles for intelligent control of contact force based on fuzzy PID control:
1. when e f When the value of (2) is larger, i.e. the target contact force and the actual contact force differ more, a larger K is set p Quickly eliminate error and select smaller K d Prevent overshoot, set K i =0 avoids integral saturation.
2. When e f When the value of (1) is small, i.e. the target contact force and the actual contact force differ less, K p ,K i Is kept better stable by proper increase of the value of (c) and, when ec f When the value of (2) is large, K should be increased d In contrast, turn down K d Is a value of (2).
e f ,ec f ,ΔK p ,ΔK i ,ΔK d The specific fuzzy inference table is as described in fig. 4.
Step four: as shown in fig. 5, when the robot-automated grinding process is performed, moment information is detected. If the torque value exceeds the reference torque value, the robot will adjust the pose to achieve constant torque control. In detail, when the moment value is greater than or less than the reference moment, the posture of the robot grinding track is adjusted to avoid overgrinding. The PD control algorithm is easy to implement and can be used to ensure constant torque control during grinding. For the reference moment, the moment is easy to be influenced by the grinding processTo the size of the workpiece model, thus taking the sum of all the previous moments as the average as the reference moment M for the control algorithm ref . The reference moment is thus defined as,
wherein Mi Is the torque detection value of the ith time.
In a word, a moment control realization force and moment fusion control strategy is added into the control strategy, so that the phenomenon of overgrinding of the starting position and the end position of a grinding path can be effectively avoided by introducing the moment control, the situation of sharp edges is caused, and the reject ratio of workpieces is increased. The force-position hybrid control strategy as described in fig. 2, where the robots X, Y, B, C dimensions employ position control, Z employ force control, a employ moment control, and the selection matrix S of the strategy is described as:
S＝diag(0,0,1,1,0,0)
for force control in process, it can be described as:
S[F p -F cg ]＝[0,0,z f ,a f ,0,0] T
for target position control, it can be described as:
X p ＝[x,y,z,a,b,c] T
[I-S]X p ＝[x,y,0,0,b,c] T
robot trajectory position X resulting from force control and position control ref Can be expressed as:
X ref ＝S[F p -F cg ]+[I-S]X p ＝[x,y,z f ,a f ,b,c] T
the position change amount Δx input to the robot controller is expressed as:
ΔX＝X ref -X s
wherein Xs Representing the current robot position.
The control algorithm of the invention is realized in an upper computer C++, the detection value of the sensor and the pose coordinate value of the robot are transmitted to the upper computer for calculation through an IP/UDP protocol in the grinding operation process of the robot, the position correction quantity of the robot in the grinding operation process is obtained, the upper computer transmits the correction value to the robot, the robot operates a workpiece to realize constant force grinding control, and the information transmission process is shown in figure 6.
The intelligent control of the contact force based on the fuzzy PID control can realize the high-precision control of the grinding contact force, and ensure that the contact force is maintained within the allowed range of the set value in the grinding process. And the quantitative removal of the material for workpiece grinding is completed according to the high-precision control of the contact force, so that the efficiency and the precision of robot automation for grinding complex curved surfaces such as blades and the like are realized. The introduction of moment control can effectively avoid over-grinding phenomena of the initial position and the final position of a grinding path and the position with larger fluctuation change of the surface of the workpiece. The control strategy of the invention has strong universality and can be suitable for grinding processing of various parts.
While the foregoing is directed to the preferred embodiments of the present invention, it will be appreciated by those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the present invention.
Claims (3)
1. An intelligent control method for a robot automatic grinding operation process is characterized by comprising the following steps:
s1, controlling the tail end of an arm of a robot to move according to a preset track position;
s2, in the motion process, detecting the contact force and moment between the workpiece and the grinding machine tool in real time through a force sensor;
s3, solving grinding contact force according to the gravity compensation of the end load of the robot; comprising the following steps:
according to the transformation relation of each coordinate system of the robot automatic grinding system, solving the load of the workpiece and other position variables, and utilizing S F＝ S G+ S F zero Performing a least square method to complete gravity compensation; wherein, S f is the contact force data actually detected by the force sensor, S g is the detected effect value of the load gravity in the force sensor coordinate system, S F zero is a force sensor detectionZero drift value of (2);
the solution of the grinding contact force is that,
wherein ,Fcg Is the required contact force +.>
Is the transformation relation of the object coordinate system to the force sensor coordinate system, < >>
Representing the transformation relation from the grinding machine coordinate system to the workpiece coordinate system;
s4, realizing robot automatic grinding force position hybrid control according to a gravity compensation result, so that the actual contact force approaches to the target value to realize robot automatic grinding; comprising the following steps:
the tail end position of a given robot controls the robot to plan a path X according to a preset track p The contact force is controlled by adopting force-position mixed control in the walking process;
the contact force control is as follows: the contact force control process adjusts the actual contact force F through force-position hybrid control cg Contact force F with target p The difference value and the planned path are corrected in real time, so that the flexible control of the tail end force of the robot is realized;
the contact force control process adopts a contact force control method based on fuzzy PID control; definition e f Is the target contact force F p With actual contact force F cg Is the difference, ec f Is e f Rate of change, ec f and ef Is the input of the fuzzy PID controller, deltaK p ,ΔK i ,ΔK d Is the proportional, integral and differential regulation parameter of PID controller, and uses fuzzy set e f ,ec f ,ΔK p ,ΔK i ,ΔK d Value of = { NB, NM, NS, ZO, PS, PM, PB }, and final output parameter K of fuzzy PID control is adjusted p 、K i 、K d : thereby realizing the actual contact force F cg Approach target contact force F p ；
And S5, simultaneously adopting torque control in the automatic grinding process, calculating the position and posture information of the next track of the robot grinding process, and realizing constant force control and force and torque fusion in the whole process.
2. The intelligent control method for the automatic grinding operation process of the robot according to claim 1, wherein the method is realized based on an intelligent control system for the automatic grinding operation process of the robot, and the system comprises an industrial robot, a force sensor, a grinding workpiece, a grinding machine tool and an upper computer; the robot is characterized in that the force sensor is fixed at the tail end of the robot through a connecting tool, the workpiece is ground and processed through the clamping of the connecting tool at the tail end of the force sensor, an instruction is transmitted between the upper computer and a driver and a sensor of the industrial robot through an IP/UDP protocol, and the upper computer controls the tail end position of an arm of the robot to realize the grinding and processing of the workpiece on a grinding machine tool.
3. The intelligent control method for a robot automated grinding process according to claim 1, wherein the calculating the next track position and posture information of the robot grinding process by using torque control in the automated grinding process comprises:
when the robot automatic grinding processing is carried out, moment information is detected in real time, and if the moment value exceeds a reference moment value, the terminal gesture of the robot is adjusted to realize constant moment control.
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