CN116872200A - Dynamic error pre-compensation method and device for parallel robot - Google Patents
Dynamic error pre-compensation method and device for parallel robot Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1615—Programme controls characterised by special kind of manipulator, e.g. planar, scara, gantry, cantilever, space, closed chain, passive/active joints and tendon driven manipulators
- B25J9/1623—Parallel manipulator, Stewart platform, links are attached to a common base and to a common platform, plate which is moved parallel to the base
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
- B25J9/163—Programme controls characterised by the control loop learning, adaptive, model based, rule based expert control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
Abstract
The application discloses a method and a device for pre-compensating dynamic errors of parallel robots, wherein the method comprises the following steps: acquiring dynamic parameters of the parallel processing robots and determining a rigid body dynamic model of the parallel processing robots; calculating theoretical driving forces of all driving shafts of the parallel processing robots based on a preset rigid body dynamics model, and inputting the theoretical driving forces into a moment feedforward channel of a servo driving system to perform dynamics feedforward control; and predicting the dynamic tracking error of the driving shaft by using a pre-constructed tracking error prediction model of the driving shaft of the parallel processing robot, and correcting the motion track in the driving space according to the dynamic tracking error so as to perform high dynamic precision control on the parallel processing robot. Therefore, the problem that the dynamic accuracy and the processing quality of the robot are difficult to guarantee due to the fact that the performance of the controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of the controlled object parallel processing robot in the related technology is solved.
Description
Technical Field
The application relates to the technical field of robots and application, in particular to a method and a device for pre-compensating dynamic errors of parallel robots.
Background
In the related art, due to the fact that the driving unit and the hinge are strictly sealed, larger friction resistance exists in the movement process of the robot, the influence of nonlinear dynamics of the robot body is superposed, and the dynamic accuracy of the robot in the movement process is difficult to guarantee, so that the dynamic accuracy of the robot can be controlled by adopting a conventional tricyclic PID (proportion-integral-derivative) controller, and dynamic errors in the reversing of a driving shaft can be reduced.
However, in the related art, the control effect is poor due to the fact that the performance of the controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of the controlled object parallel processing robot, so that the dynamic accuracy and the processing quality of the robot are difficult to guarantee, and the problem needs to be solved.
Disclosure of Invention
The present application is based on the inventors' knowledge and knowledge of the following problems:
in the technical fields of aerospace, energy sources and the like, as the design level is mature, the complexity of parts is improved continuously, the severe requirements are put forward on the performance of processing equipment in the aspects of composite angle processing and high finish processing, the parallel processing robot can avoid singular fields in a gesture working space by reasonably configuring mechanism configurations, and the parallel processing robot can be used as an effective supplement of a traditional serial machine tool and is applied to processing complex parts with complex curved surface characteristics.
Because in the course of the work, robot end effector motion law is complicated, needs adjustment position and gesture simultaneously, leads to the frequent switching-over of drive shaft frequent acceleration and deceleration, in addition, there is cutting fluid, the smear metal splashes in the course of the working, in order to protect equipment safety, can carry out the strict seal to drive unit and hinge usually to lead to the robot to have great frictional resistance in the course of the motion, the influence of superimposed robot body nonlinear dynamics, lead to the robot to be difficult to guarantee in the motion in-process dynamic accuracy, especially dynamic error is great when the drive shaft switching-over, influence machining accuracy.
The conventional tricyclic PID controller is usually adopted to control the dynamic accuracy of the robot in the prior art, but the nonlinear dynamics characteristic and the nonlinear friction characteristic of the parallel processing robot of the controller and the controlled object are not matched, so that a satisfactory control effect is difficult to realize, and improvement is needed.
The application provides a method and a device for pre-compensating dynamic errors of parallel robots, which are used for solving the problem that the dynamic accuracy and the processing quality of the robots are difficult to guarantee due to the fact that the performance of a controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of the parallel processing robots of controlled objects in the related technology.
An embodiment of a first aspect of the present application provides a method for pre-compensating a dynamic error of a parallel robot, including the steps of: acquiring dynamic parameters of parallel processing robots and determining a rigid body dynamic model of the parallel processing robots; calculating theoretical driving forces of all driving shafts of the parallel processing robots based on a preset rigid body dynamics model, and inputting the theoretical driving forces into a moment feedforward channel of a servo driving system to perform dynamics feedforward control; and estimating the dynamic tracking error of the driving shaft by using a pre-constructed tracking error estimation model of the driving shaft of the parallel processing robot, and correcting the motion track in the driving space according to the dynamic tracking error so as to control the parallel processing robot with high dynamic precision.
Optionally, in one embodiment of the present application, before estimating the tracking error of the driving shaft, the method further includes: the single-degree-of-freedom servo driving system is based on a plurality of time-varying loads determined by the parallel processing robot, wherein a position loop of the single-degree-of-freedom servo driving system adopts a proportional controller, a speed loop adopts a proportional-integral controller, a current loop adopts a proportional controller, a controlled object is a motor rotor, the controlled object is used as a first-order inertia element, the time-varying loads caused in the motion process of a mechanical body of the parallel processing robot act on an output end of the current loop and are used as disturbance of the control system, speed feedforward is added at an input port of the speed loop, and moment feedforward is added at an input port of the current loop;
Wherein, according to the single degree of freedom servo drive control system, deducing a dynamic error transfer function as follows:
E(s)＝E load (s)+E input (s)＝G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)，
wherein ,Eload (s) is the firstSource, E input (s) is of a second origin, G eload (s) is the error transfer function of the first source, G einput (s) is the error transfer function of the second source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop, Q d (s) is a motion command input to the drive shaft;
establishing a tracking error pre-estimation model of the parallel processing robot drive shaft to determine a tracking error source, wherein the tracking error source comprises a first source caused by dynamic characteristics of the parallel processing robot and a second source caused by characteristics of a motor closed-loop feedback control system;
the first source is:
E load (s)＝G eload (s)(K t T ff (s)-T L (s))，
wherein ,Geload (s) is the error transfer function of the first source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop,
the second source is:
E input (s)＝G einput (s)Q d (s)，
wherein ,Geinput (s) is the error transfer function of the second source, Q d And(s) is a motion command input to the drive shaft.
Optionally, in an embodiment of the present application, after determining the source of tracking error, the method further includes: generating a dynamic accuracy control strategy which is formed by combining a dynamic feedforward method and a dynamic tracking error precompensation method according to the tracking error source, wherein the dynamic accuracy control strategy comprises the steps of eliminating dynamic errors caused by the dynamic characteristics of a robot by utilizing a target dynamic feedforward control method and compensating the dynamic tracking errors caused by the characteristics of a closed-loop feedback control system of a motor by utilizing a target dynamic tracking error precompensation method.
Optionally, in one embodiment of the present application, the tracking error estimation model is:
wherein ,k is a dynamic tracking error predictive value caused by the characteristics of a closed loop feedback system ev Estimating coefficients for the velocity term,/->For the speed of movement input to the drive shaft, K ea Estimating the coefficient for the acceleration term,/->For the motion acceleration input to the drive shaft, t is the interpolation time.
Optionally, in an embodiment of the present application, the estimating the dynamic tracking error of the driving shaft by using a pre-constructed tracking error estimation model of the driving shaft of the parallel processing robot, and correcting the motion trail in the driving space according to the dynamic tracking error includes: obtaining an instruction track of a robot end tool of the parallel processing robot; transforming the command track into a command track of the driving shafts according to inverse kinematics of the parallel processing robots, wherein the command track comprises the position, the speed and the acceleration of each driving shaft; obtaining a dynamic tracking error estimated value of the driving shaft in each control period according to the driving shaft dynamic tracking error estimated model; and adding the same offset as the dynamic tracking error predicted value to the command track to obtain a corrected driving shaft command track, wherein the position of the corrected driving shaft command track is as follows:
wherein ,Lr (t) is the position of the drive shaft,a dynamic tracking error pre-estimation value;
and sending the corrected driving shaft command track to a servo driving system for execution.
An embodiment of a second aspect of the present application provides a dynamic error precompensation device for a parallel robot, including: the acquisition module is used for acquiring dynamic parameters of the parallel processing robots and determining a rigid body dynamic model of the parallel processing robots; the calculation module is used for calculating the theoretical driving force of each driving shaft of the parallel processing robot based on a preset rigid body dynamics model, and inputting the theoretical driving force into a moment feedforward channel of a servo driving system so as to perform dynamics feedforward control; the estimating module is used for estimating the dynamic tracking error of the driving shaft by utilizing a pre-constructed tracking error estimating model of the driving shaft of the parallel processing robot and correcting the motion track in the driving space according to the dynamic tracking error so as to control the parallel processing robot with high dynamic precision.
Optionally, in an embodiment of the present application, the apparatus of the embodiment of the present application further includes: the establishment module is used for estimating the tracking error of the driving shaft, based on a single-degree-of-freedom servo driving system under the action of a plurality of time-varying loads determined by the parallel processing robot, wherein a position loop of the single-degree-of-freedom servo driving system adopts a proportional controller, a speed loop adopts a proportional-integral controller, a current loop adopts a proportional controller, a controlled object is a motor rotor, the controlled object is used as a first-order inertia element, the time-varying loads caused in the motion process of the mechanical body of the parallel processing robot act on the output end of the current loop and are used as disturbance of the control system, speed feedforward is added at an input port of the speed loop, moment feedforward is added at an input port of the current loop,
Wherein, according to the single degree of freedom servo drive control system, deducing a dynamic error transfer function as follows:
E(s)＝E load (s)+E input (s)＝G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)，
wherein ,Eload (s) is the first source, E input (s) is of a second origin, G eload (s) is the error transfer function of the first source, G einput (s) is the error transfer function of the second source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop, Q d (s) a motion command input to the drive shaft,
establishing a tracking error estimation model of the parallel processing robot drive shaft to determine a tracking error source, wherein the tracking error source comprises a first source caused by dynamics of the parallel processing robot and a second source caused by characteristics of a motor closed loop feedback control system,
the first source is:
E load (s)＝G eload (s)(K t T ff (s)-T L (s))，
wherein ,Geload (s) is the error transfer function of the first source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop,
the second source is:
E input (s)＝G einput (s)Q d (s)，
wherein ,Geinput (s) is the error transfer function of the second source, Q d And(s) is a motion command input to the drive shaft.
Optionally, in an embodiment of the present application, the apparatus of the embodiment of the present application further includes: and the generation module is used for generating a dynamic precision control strategy which is formed by combining a dynamic feedforward method and a dynamic tracking error precompensation method according to the tracking error source after the tracking error source is determined, wherein the dynamic precision control strategy comprises the steps of eliminating the dynamic error caused by the dynamic characteristic of the robot by utilizing a target dynamic feedforward control method and compensating the dynamic tracking error caused by the characteristic of a closed-loop feedback control system of a motor by utilizing a target dynamic tracking error precompensation method.
Optionally, in one embodiment of the present application, the tracking error estimation model is:
wherein ,k is a dynamic tracking error predictive value caused by the characteristics of a closed loop feedback system ev Estimating coefficients for the velocity term,/->For the speed of movement input to the drive shaft, K ea Estimating the coefficient for the acceleration term,/->For the motion acceleration input to the drive shaft, t is the interpolation time.
Optionally, in one embodiment of the present application, the estimating module includes: the first acquisition unit is used for acquiring the instruction track of the robot end tool of the parallel processing robot; the conversion unit is used for converting the command track into a command track of the driving shafts according to inverse kinematics of the parallel processing robots, wherein the command track comprises the position, the speed and the acceleration of each driving shaft; the second acquisition unit is used for acquiring a dynamic tracking error estimated value of the driving shaft in each control period according to the driving shaft dynamic tracking error estimated model; a third obtaining unit, configured to obtain a corrected driving shaft instruction track by adding the same offset as the dynamic tracking error estimated value to the instruction track, where the position of the corrected driving shaft instruction track is:
wherein ,Lr (t) is the position of the drive shaft,a dynamic tracking error pre-estimation value;
and the sending unit is used for sending the corrected driving shaft command track to a servo driving system for execution.
An embodiment of a third aspect of the present application provides an electronic device, including: the system comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to realize the parallel robot dynamic error pre-compensation method according to the embodiment.
A fourth aspect of the present application provides a computer readable storage medium storing a computer program which when executed by a processor implements a parallel robot dynamic error pre-compensation method as above.
According to the embodiment of the application, the dynamic parameters of the parallel processing robots can be obtained, the rigid body dynamic model of the parallel processing robots is determined, the theoretical driving force of each driving shaft of the parallel processing robots is calculated, and the theoretical driving force is input into the moment feedforward channel of the servo driving system to perform dynamic feedforward control, and the dynamic tracking error of the driving shafts is estimated by utilizing the pre-built tracking error estimation model of the driving shafts of the parallel processing robots, so that the motion trail is corrected in the driving space to perform high dynamic precision control on the parallel processing robots, and further the dynamic precision and the processing quality of the robots are improved. Therefore, the problem that the dynamic accuracy and the processing quality of the robot are difficult to guarantee due to the fact that the performance of the controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of the controlled object parallel processing robot in the related technology is solved.
Additional aspects and advantages of the application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the application.
Drawings
The foregoing and/or additional aspects and advantages of the application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a flow chart of a method for pre-compensating dynamic errors of a parallel robot according to an embodiment of the present application;
FIG. 2 is a schematic diagram of the dynamic error pre-compensation principle according to an embodiment of the present application;
FIG. 3 is a schematic view of a wavy path and a feed rate corresponding to each point on the path according to an embodiment of the application;
FIG. 4 is a schematic diagram of a command trajectory of a robot tip according to an embodiment of the present application;
FIG. 5 is a schematic diagram of a dynamic tracking error estimation curve of a driving shaft when a robot tracks a wavy path according to an embodiment of the application;
FIG. 6 is a schematic diagram of a single axis servo drive control system under time varying load in accordance with an embodiment of the present application;
fig. 7 is a schematic structural diagram of a dynamic error precompensation device for parallel robots according to an embodiment of the present application;
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative and intended to explain the present application and should not be construed as limiting the application.
The method and the device for pre-compensating the dynamic errors of the parallel robot are described below with reference to the accompanying drawings. Aiming at the problem that the dynamic accuracy and the processing quality of a robot are difficult to guarantee due to the fact that the performance of a controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of a parallel processing robot of a controlled object in the related technology mentioned in the background center, the application provides a dynamic error pre-compensation method of the parallel processing robot. Therefore, the problem that the dynamic accuracy and the processing quality of the robot are difficult to guarantee due to the fact that the performance of the controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of the controlled object parallel processing robot in the related technology is solved.
Specifically, fig. 1 is a schematic flow chart of a method for pre-compensating dynamic errors of a parallel robot according to an embodiment of the present application.
As shown in fig. 1, the method for pre-compensating the dynamic error of the parallel robot comprises the following steps:
in step S101, dynamic parameters of the parallel processing robot are acquired, and a rigid body dynamic model of the parallel processing robot is determined.
It can be appreciated that the embodiment of the application can acquire the dynamic parameters of the parallel processing robot, for example, the dynamic parameter identification of the parallel processing robot can be carried out to determine the rigid body dynamic model of the parallel processing robot, thereby effectively improving the performability of the dynamic error precompensation of the parallel processing robot.
In step S102, theoretical driving forces of the respective drive shafts of the parallel processing robots are calculated based on a preset rigid body dynamics model, and the theoretical driving forces are input to a moment feedforward path of the servo driving system to perform dynamics feedforward control.
It can be understood that the embodiment of the application can calculate the theoretical driving force of each driving shaft of the parallel processing robot in real time based on the rigid body dynamics model, and input the theoretical driving force into the moment feedforward channel of the servo driving system, so as to complete dynamics feedforward control and effectively reduce dynamic tracking errors.
Further, after the processing dynamics feedforward, dynamic tracking errors caused by nonlinear dynamics characteristics and nonlinear friction of the robot are greatly reduced, dynamic errors of all driving shafts in the robot motion process are dominated by tracking errors caused by characteristics of a closed-loop feedback control system, the tracking errors are in linear relation with the speed and acceleration of the driving shaft motion, and the tracking errors can be accurately estimated before actual motion.
In step S103, a pre-constructed tracking error estimation model of the driving shaft of the parallel processing robot is used to estimate the dynamic tracking error of the driving shaft, and the motion track is corrected in the driving space according to the dynamic tracking error, so as to perform high dynamic precision control on the parallel processing robot.
It can be understood that the embodiment of the application can utilize the pre-constructed tracking error prediction model of the driving shaft of the parallel processing robot to predict the dynamic tracking error of the driving shaft and correct the motion track in the driving space according to the dynamic tracking error, thereby carrying out high dynamic precision control on the parallel processing robot and further effectively improving the dynamic precision and the processing quality of the robot.
In one embodiment of the present application, a pre-constructed tracking error estimation model of a parallel processing robot driving shaft is used to estimate a dynamic tracking error of the driving shaft, and correct a motion track in a driving space according to the dynamic tracking error, including: obtaining an instruction track of a robot end tool of the parallel processing robot; transforming the command track into a command track of the driving shafts according to inverse kinematics of the parallel processing robots, wherein the command track comprises the position, the speed and the acceleration of each driving shaft; obtaining a dynamic tracking error estimated value of the driving shaft in each control period according to the driving shaft dynamic tracking error estimated model; and adding the same offset as the dynamic tracking error predicted value on the command track to obtain a corrected command track of the driving shaft, wherein the corrected command track of the driving shaft is positioned as follows:
wherein ,Lr (t) is the position of the drive shaft,a dynamic tracking error pre-estimation value;
and sending the corrected driving shaft command track to a servo driving system for execution.
For example, as shown in fig. 2, which is a schematic diagram of dynamic error precompensation according to an embodiment of the present application, the embodiment of the present application may obtain, for a wave-shaped processing path, a command track of a tool at a robot end through processing track planning, and particularly as shown in fig. 3 and fig. 4, where fig. 3 is the wave-shaped processing path and a feed speed f corresponding to each point on the path, and fig. 4 is the command track of the robot end, including a command position p, a command speed v and a command acceleration a.
Then, the command trajectory of the robot tip may be converted into a driveshaft space, and the command trajectory of the driveshaft may be obtained, which may include a driveshaft position L r (t) drive shaft speedAcceleration of the drive shaft->As shown in FIG. 5, the estimated dynamic tracking error value of each drive axis can be obtained from the drive axis dynamic tracking error estimation model in the following steps>
Next, the command trajectory of the drive shaft may be corrected by a precompensation method, which is obtained according to the following relationCorrected drive shaft command position L c (t), namely:
wherein ,Lr (t) is the position of the drive shaft,the dynamic tracking error is predicted.
And furthermore, the robot motion is controlled by adopting the corrected driving shaft motion trail, so that the dynamic accuracy of the robot is effectively improved.
Optionally, in one embodiment of the present application, before estimating the tracking error of the drive shaft, the method further includes: the single degree of freedom servo driving system based on the multiple time-varying loads determined by the parallel processing robot, wherein, the position loop of the single degree of freedom servo driving system adopts a proportional controller, the speed loop adopts a proportional-integral controller, the current loop adopts a proportional controller, the controlled object is a motor rotor, the controlled object is used as a first-order inertia element, the time-varying loads caused by the motion process of the mechanical body of the parallel processing robot act on the output end of the current loop and are used as disturbance of the control system, the speed feedforward is added at the input port of the speed loop, the moment feedforward is added at the input port of the current loop,
wherein, according to single degree of freedom servo drive control system, derive dynamic error transfer function as:
E(s)＝E load (s)+E input (s)＝G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)，
wherein ,Eload (s) is the first source, E input (s) is of a second origin, G eload (s) is the error transfer function of the first source, G einput (s) is the error transfer function of the second source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop, Q d (s) is the inputA movement command is entered into the drive shaft,
establishing a tracking error estimation model of the parallel processing robot drive shaft to determine a source of tracking error, wherein the source of tracking error comprises a first source caused by the dynamics of the parallel processing robot and a second source caused by the characteristics of the motor closed loop feedback control system,
the first source is:
E load (s)＝G eload (s)(K t T ff (s)-T L (s))，
wherein ,Geload (s) is the error transfer function of the first source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop,
the second source is:
E input (s)＝G einput (s)Q d (s)，
wherein ,Geinput (s) is the error transfer function of the second source, Q d And(s) is a motion command input to the drive shaft.
As a possible implementation manner, the embodiment of the application can consider the parallel processing robot as a single-degree-of-freedom servo driving system under the action of a plurality of time-varying loads, a tracking error prediction model of a driving shaft of the parallel processing robot is established, and according to the tracking error prediction model, the tracking error of the driving shaft of the parallel processing robot mainly comprises two sources, one of which is caused by the nonlinear dynamics characteristic and the nonlinear friction of the robot, and the other of which is caused by the characteristic of a closed-loop feedback control system, so that the feasibility of the dynamic error precompensation of the parallel processing robot is improved.
For example, as shown in fig. 6, the embodiment of the application can use the parallel processing robot as a single-axis servo driving system under the action of five time-varying loads, fig. 6 is a control frame of each single-axis servo driving control system, the basic control framework of the single-axis servo driving system is conventional three-loop PID control, the position loop adopts a proportional controller, the speed loop adopts a proportional-integral controller, the current loop adopts a proportional controller, the controlled object is a motor rotor, the controlled object can be used as a first-order inertia element, the time-varying load caused in the motion process of the robot mechanical body acts on the output end of the current loop and can be used as disturbance of the control system, in order to promote the response speed of the servo system, speed feedforward can be added at the input port of the speed loop, and moment feedforward is added at the input port of the current loop.
The dynamic error transfer function can then be derived from the servo drive control system block diagram:
E(s)＝E load (s)+E input (s)＝G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)，
therefore, the dynamic tracking error of the servo driving system includes two sources, the first source is the tracking error caused by the time-varying load, namely:
E load (s)＝G eload (s)(K t T ff (s)-T L (s))，
wherein ,Geload (s) is the error transfer function of the first source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop,
the second source is the dynamic tracking error caused by the characteristics of the closed loop feedback control system, namely:
E input (s)＝G einput (s)Q d (s)，
wherein ,Geinput (s) is the error transfer function of the second source, Q d And(s) is a motion command input to the drive shaft.
Wherein, the dynamic tracking error of the second source is related to the motion command input to the driving shaft, and the dynamic tracking error estimation model can be organized into the following time domain equation, namely:
wherein ,k is a dynamic tracking error predictive value caused by the characteristics of a closed loop feedback system ev Estimating coefficients for the velocity term,/->For the speed of movement input to the drive shaft, K ea Estimating the coefficient for the acceleration term,/->For the motion acceleration input to the drive shaft, t is the interpolation time.
Optionally, in one embodiment of the present application, after determining the source of the tracking error, the method further includes: and generating a dynamic accuracy control strategy by combining a dynamic feedforward and dynamic tracking error precompensation method according to a tracking error source, wherein the dynamic accuracy control strategy comprises the steps of eliminating dynamic errors caused by the dynamic characteristics of the robot by utilizing a target dynamic feedforward control method and compensating dynamic tracking errors caused by the characteristics of a closed-loop feedback control system of a motor by utilizing a target dynamic tracking error precompensation method.
In some embodiments, the embodiments of the present application may establish a dynamic accuracy control strategy that combines a dynamic feedforward and a dynamic tracking error precompensation method according to a tracking error source, and reduce or eliminate tracking errors caused by nonlinear dynamics characteristics and nonlinear friction by using the dynamic feedforward, and reduce tracking errors caused by characteristics of a closed-loop feedback control system by using the dynamic error precompensation method.
According to the dynamic error pre-compensation method for the parallel robot, which is provided by the embodiment of the application, the dynamic parameters of the parallel processing robot can be obtained, the rigid body dynamic model of the parallel processing robot is determined, the theoretical driving force of each driving shaft of the parallel processing robot is calculated, the theoretical driving force is input into the moment feedforward channel of the servo driving system to perform dynamic feedforward control, and the dynamic tracking error of the driving shaft is estimated by utilizing the pre-built tracking error estimated model of the driving shaft of the parallel processing robot, so that the motion trail is corrected in the driving space, the high dynamic precision control is performed on the parallel processing robot, the dynamic precision of the robot is further improved, and the processing quality is improved. Therefore, the problem that the dynamic accuracy and the processing quality of the robot are difficult to guarantee due to the fact that the performance of the controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of the controlled object parallel processing robot in the related technology is solved.
Next, a parallel robot dynamic error pre-compensation device according to an embodiment of the present application will be described with reference to the accompanying drawings.
Fig. 7 is a block schematic diagram of a dynamic error precompensation device for a parallel robot according to an embodiment of the present application.
As shown in fig. 7, the parallel robot dynamic error precompensation device 10 includes: the device comprises an acquisition module 100, a calculation module 200 and an estimation module 300.
Specifically, the obtaining module 100 is configured to obtain a kinetic parameter of the parallel processing robot, and determine a rigid body kinetic model of the parallel processing robot.
The calculation module 200 is configured to calculate a theoretical driving force of each driving shaft of the parallel processing robot based on a preset rigid body dynamics model, and input the theoretical driving force to a moment feedforward channel of the servo driving system for dynamics feedforward control.
The estimating module 300 is configured to estimate a dynamic tracking error of the driving shaft by using a pre-constructed tracking error estimating model of the driving shaft of the parallel processing robot, and correct a motion track in a driving space according to the dynamic tracking error, so as to perform high dynamic precision control on the parallel processing robot.
Optionally, in an embodiment of the present application, the apparatus 10 of the embodiment of the present application further includes: and (5) establishing a module.
Wherein, the establishment module is used for estimating the tracking error of the driving shaft, based on the single degree of freedom servo driving system under the action of a plurality of time-varying loads determined by the parallel processing robot, wherein, the position loop of the single degree of freedom servo driving system adopts a proportional controller, the speed loop adopts a proportional-integral controller, the current loop adopts a proportional controller, the controlled object is a motor rotor, the controlled object is a first-order inertia element, the time-varying loads caused by the motion process of the mechanical body of the parallel processing robot act on the output end of the current loop and serve as the disturbance of the control system, the speed feedforward is added at the input port of the speed loop, the moment feedforward is added at the input port of the current loop,
wherein, according to single degree of freedom servo drive control system, derive dynamic error transfer function as:
E(s)＝E load (s)+E input (s)＝G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)，
wherein ,Eload (s) is the first source, E input (s) is of a second origin, G eload (s) is the error transfer function of the first source, G einput (s) is the error transfer function of the second source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop, Q d (s) a motion command input to the drive shaft,
establishing a tracking error estimation model of the parallel processing robot drive shaft to determine a source of tracking error, wherein the source of tracking error comprises a first source caused by the dynamics of the parallel processing robot and a second source caused by the characteristics of the motor closed loop feedback control system,
The first source is:
E load (s)＝G eload (s)(K t T ff (s)-T L (s))，
wherein ,Geload (s) is the error transfer function of the first source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop,
the second source is:
E input (s)＝G einput (s)Q d (s)，
wherein ,Geinput (s) is the error transfer function of the second source, Q d And(s) is a motion command input to the drive shaft.
Optionally, in an embodiment of the present application, the apparatus 10 of the embodiment of the present application further includes: and generating a module.
The generation module is used for generating a dynamic accuracy control strategy which is formed by combining a dynamic feedforward method and a dynamic tracking error precompensation method according to the tracking error source after the tracking error source is determined, wherein the dynamic accuracy control strategy comprises the steps of eliminating dynamic errors caused by the dynamic characteristics of the robot by utilizing a target dynamic feedforward control method and compensating dynamic tracking errors caused by the characteristics of a closed loop feedback control system of a motor by utilizing the target dynamic tracking error precompensation method.
Optionally, in one embodiment of the present application, the tracking error estimation model is:
wherein ,k is a dynamic tracking error predictive value caused by the characteristics of a closed loop feedback system ev Estimating coefficients for the velocity term,/->For the speed of movement input to the drive shaft, K ea Estimating the coefficient for the acceleration term,/->For the motion acceleration input to the drive shaft, t is the interpolation time.
Optionally, in one embodiment of the present application, the estimation module 300 includes: the device comprises a first acquisition unit, a conversion unit, a second acquisition unit, a third acquisition unit and a sending unit.
The first acquisition unit is used for acquiring the instruction track of the robot end tool of the parallel processing robot.
And the conversion unit is used for converting the command track into a command track of the driving shafts according to inverse kinematics of the parallel processing robots, wherein the command track comprises the position, the speed and the acceleration of each driving shaft.
And the second acquisition unit is used for acquiring a dynamic tracking error estimated value of the driving shaft in each control period according to the driving shaft dynamic tracking error estimated model.
The third obtaining unit is configured to obtain a corrected driving shaft instruction track by adding the same offset as the dynamic tracking error predicted value to the instruction track, where the position of the corrected driving shaft instruction track is:
wherein ,Lr (t) is the position of the drive shaft,the dynamic tracking error is predicted.
And the sending unit is used for sending the corrected driving shaft command track to the servo driving system for execution.
It should be noted that the foregoing explanation of the embodiment of the method for pre-compensating the dynamic error of the parallel robot is also applicable to the device for pre-compensating the dynamic error of the parallel robot in this embodiment, and will not be repeated here.
According to the dynamic error pre-compensation device for the parallel robot, which is provided by the embodiment of the application, the dynamic parameters of the parallel processing robot can be obtained, the rigid body dynamic model of the parallel processing robot is determined, the theoretical driving force of each driving shaft of the parallel processing robot is calculated, the theoretical driving force is input into the moment feedforward channel of the servo driving system to perform dynamic feedforward control, and the dynamic tracking error of the driving shaft is estimated by utilizing the pre-built tracking error estimated model of the driving shaft of the parallel processing robot, so that the motion trail is corrected in the driving space, the high dynamic precision control is performed on the parallel processing robot, and the dynamic precision and the processing quality of the robot are further improved. Therefore, the problem that the dynamic accuracy and the processing quality of the robot are difficult to guarantee due to the fact that the performance of the controller is not matched with the nonlinear dynamics characteristic and the nonlinear friction characteristic of the controlled object parallel processing robot in the related technology is solved.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
a memory 801, a processor 802, and a computer program stored on the memory 801 and executable on the processor 802.
The processor 802 implements the parallel robot dynamic error pre-compensation method provided in the above embodiment when executing a program.
Further, the electronic device further includes:
a communication interface 803 for communication between the memory 801 and the processor 802.
A memory 801 for storing a computer program executable on the processor 802.
The memory 801 may include high-speed RAM memory or may further include non-volatile memory (non-volatile memory), such as at least one magnetic disk memory.
If the memory 801, the processor 802, and the communication interface 803 are implemented independently, the communication interface 803, the memory 801, and the processor 802 may be connected to each other through a bus and perform communication with each other. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 8, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 801, the processor 802, and the communication interface 803 are integrated on a chip, the memory 801, the processor 802, and the communication interface 803 may communicate with each other through internal interfaces.
The processor 802 may be a central processing unit (Central Processing Unit, abbreviated as CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more integrated circuits configured to implement embodiments of the present application.
The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the parallel robot dynamic error pre-compensation method as above.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, for example, two, three, etc., unless specifically defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and additional implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order from that shown or discussed, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
Logic and/or steps represented in the flowcharts or otherwise described herein, e.g., a ordered listing of executable instructions for implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer cartridge (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may be electronically captured, via optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It is to be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or a portion of the steps carried out in the method of the above-described embodiments may be implemented by a program to instruct related hardware, where the program may be stored in a computer readable storage medium, and where the program, when executed, includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented in the form of software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like. While embodiments of the present application have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the application, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the application.
Claims (10)
1. The method for pre-compensating the dynamic errors of the parallel robots is characterized by comprising the following steps of:
acquiring dynamic parameters of parallel processing robots and determining a rigid body dynamic model of the parallel processing robots;
calculating theoretical driving forces of all driving shafts of the parallel processing robots based on a preset rigid body dynamics model, and inputting the theoretical driving forces into a moment feedforward channel of a servo driving system to perform dynamics feedforward control; and
and estimating the dynamic tracking error of the driving shaft by using a pre-constructed tracking error estimation model of the driving shaft of the parallel processing robot, and correcting the motion track in the driving space according to the dynamic tracking error so as to control the parallel processing robot with high dynamic precision.
2. The parallel robot dynamic error pre-compensation method of claim 1, further comprising, prior to estimating the tracking error of the drive shaft:
the single-degree-of-freedom servo driving system is based on a plurality of time-varying loads determined by the parallel processing robot, wherein a position loop of the single-degree-of-freedom servo driving system adopts a proportional controller, a speed loop adopts a proportional-integral controller, a current loop adopts a proportional controller, a controlled object is a motor rotor, the controlled object is used as a first-order inertia element, the time-varying loads caused in the motion process of a mechanical body of the parallel processing robot act on an output end of the current loop and are used as disturbance of the control system, speed feedforward is added at an input port of the speed loop, and moment feedforward is added at an input port of the current loop;
wherein, according to the single degree of freedom servo drive control system, deducing a dynamic error transfer function as follows:
E(s)＝E load (s)+E input (s)＝G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)，
wherein ,Eload (s) is the first source, E input (s) is of a second origin, G eload (s) is the error transfer function of the first source, G einput (s) is the error transfer function of the second source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop, Q d (s) is a motion command input to the drive shaft;
establishing a tracking error pre-estimation model of the parallel processing robot drive shaft to determine a tracking error source, wherein the tracking error source comprises a first source caused by dynamic characteristics of the parallel processing robot and a second source caused by characteristics of a motor closed-loop feedback control system;
the first source is:
E load (s)＝G eload (s)(K t T ff (s)-T L (s))，
wherein ,Geload (s) is the error transfer function of the first source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop,
the second source is:
E input (s)＝G einput (s)Q d (s)，
wherein ,Geinput (s) is the error transfer function of the second source, Q d And(s) is a motion command input to the drive shaft.
3. The parallel robot dynamic error pre-compensation method of claim 2, further comprising, after determining the source of tracking error:
generating a dynamic accuracy control strategy which is formed by combining a dynamic feedforward method and a dynamic tracking error precompensation method according to the tracking error source, wherein the dynamic accuracy control strategy comprises the steps of eliminating dynamic errors caused by the dynamic characteristics of a robot by utilizing a target dynamic feedforward control method and compensating the dynamic tracking errors caused by the characteristics of a closed-loop feedback control system of a motor by utilizing a target dynamic tracking error precompensation method.
4. The method for pre-compensating dynamic errors of parallel robots according to claim 1, wherein the tracking error estimation model is:
wherein ,k is a dynamic tracking error predictive value caused by the characteristics of a closed loop feedback system ev Estimating coefficients for the velocity term,/->For the speed of movement input to the drive shaft, K ea Estimating the coefficient for the acceleration term,/->For the motion acceleration input to the drive shaft, t is the interpolation time.
5. The method for pre-compensating dynamic errors of parallel robots according to claim 1, wherein the estimating the dynamic tracking errors of the drive shafts by using a pre-constructed model for estimating the tracking errors of the drive shafts of the parallel processing robots, and correcting the motion trajectories in the drive space according to the dynamic tracking errors, comprises:
obtaining an instruction track of a robot end tool of the parallel processing robot;
transforming the command track into a command track of the driving shafts according to inverse kinematics of the parallel processing robots, wherein the command track comprises the position, the speed and the acceleration of each driving shaft;
obtaining a dynamic tracking error estimated value of the driving shaft in each control period according to the driving shaft dynamic tracking error estimated model;
And adding the same offset as the dynamic tracking error predicted value to the command track to obtain a corrected driving shaft command track, wherein the position of the corrected driving shaft command track is as follows:
wherein ,Lr (t) is the position of the drive shaft,a dynamic tracking error pre-estimation value;
and sending the corrected driving shaft command track to a servo driving system for execution.
6. A parallel robot dynamic error precompensation device, comprising:
the acquisition module is used for acquiring dynamic parameters of the parallel processing robots and determining a rigid body dynamic model of the parallel processing robots;
the calculation module is used for calculating the theoretical driving force of each driving shaft of the parallel processing robot based on a preset rigid body dynamics model, and inputting the theoretical driving force into a moment feedforward channel of a servo driving system so as to perform dynamics feedforward control; and
the estimating module is used for estimating the dynamic tracking error of the driving shaft by utilizing a pre-constructed tracking error estimating model of the driving shaft of the parallel processing robot and correcting the motion track in the driving space according to the dynamic tracking error so as to control the parallel processing robot with high dynamic precision.
7. The parallel robot dynamic error precompensation device of claim 6, further comprising:
the establishment module is used for estimating the tracking error of the driving shaft, based on a single-degree-of-freedom servo driving system under the action of a plurality of time-varying loads determined by the parallel processing robot, wherein a position loop of the single-degree-of-freedom servo driving system adopts a proportional controller, a speed loop adopts a proportional-integral controller, a current loop adopts a proportional controller, a controlled object is a motor rotor, the controlled object is used as a first-order inertia element, the time-varying loads caused in the motion process of the mechanical body of the parallel processing robot act on the output end of the current loop and are used as disturbance of the control system, speed feedforward is added at an input port of the speed loop, moment feedforward is added at an input port of the current loop,
wherein, according to the single degree of freedom servo drive control system, deducing a dynamic error transfer function as follows:
E(s)＝E load (s)+E input (s)＝G eload (s)(K t T ff (s)-T L (s))+G einput (s)Q d (s)，
wherein ,Eload (s) is the first source, E input (s) is of a second origin, G eload (s) is the error transfer function of the first source, G einput (s) is the error transfer function of the second source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop, Q d (s) a motion command input to the drive shaft,
establishing a tracking error estimation model of the parallel processing robot drive shaft to determine a tracking error source, wherein the tracking error source comprises a first source caused by the parallel processing robot dynamics and a second source caused by the motor closed loop feedback control system characteristics,
the first source is:
E load (s)＝G eload (s)(K t T ff (s)-T L (s))，
wherein ,Geload (s) is the error transfer function of the first source, K t Is the moment coefficient of the current loop, T ff (s) moment feedforward for adding control system, T L (s) is a time-varying load acting on the output of the current loop,
the second source is:
E input (s)＝G einput (s)Q d (s)，
wherein ,Geinput (s) is the error transfer function of the second source, Q d (s) is a motion instruction input to the drive shaft。
8. The device for pre-compensating dynamic errors of parallel robots according to claim 7, wherein,
and the generation module is used for generating a dynamic precision control strategy which is formed by combining a dynamic feedforward method and a dynamic tracking error precompensation method according to the tracking error source after the tracking error source is determined, wherein the dynamic precision control strategy comprises the steps of eliminating the dynamic error caused by the dynamic characteristic of the robot by utilizing a target dynamic feedforward control method and compensating the dynamic tracking error caused by the characteristic of a closed-loop feedback control system of a motor by utilizing a target dynamic tracking error precompensation method.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the parallel robot dynamic error pre-compensation method according to any one of claims 1-5.
10. A computer readable storage medium having stored thereon a computer program, characterized in that the program is executed by a processor for implementing a parallel robot dynamic error pre-compensation method according to any of claims 1-5.
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