A Double Phase Lead Compensation Iterative Learning Control Method for Manipulator System
An iterative learning control and phase advance technology, which is applied in the field of double phase advance compensation iterative learning control of robotic arm systems, can solve the problems of reducing system learning bandwidth and reducing ILC convergence accuracy, so as to improve transient learning performance and expand learning. Bandwidth, the effect of improving the convergence speed
Active Publication Date: 2022-03-04
HUAQIAO UNIVERSITY
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However, the introduced filter introduces a new phase delay that significantly reduces the ILC convergence accuracy and reduces the system learning bandwidth
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[0034] The main purpose of iterative learning control is to modify the system input through the learning law, so that the system output can track the desired output. The robot arm system model is as follows:
[0035]
[0036] where n∈[0,N] is the system running time index, k is the number of iterations, x k (n), u k (n),y k (n) respectively represent the system state, input and output at the kth iteration of the system, w k (n) represents the random disturbance of the system at the kth iteration; A, B, and C are system matrices.
[0037] Assume that the initial state of the robotic arm system (1) is the same for each iteration.
[0038] The ILC tracking error of the kth system operation is
[0039] e k (n)=y d (n)-y k (n), (1)
[0040] Its z-field expression is
[0041] E. k (z)=Y d (z)-Y k (z), (2)
[0042] Among them, y d (n) and Y d (z) are the expected output of the system in time domain and z domain respectively, Y k (z) is the z domain expression outp...
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The present invention provides a dual phase lead compensation iterative learning control method for a manipulator system, comprising the following steps: establishing a double phase lead compensation iterative learning law, determining the order of the double phase lead compensation according to the convergence condition of the manipulator system model, Then determine the correction value of the double phase lead compensation order according to the value of the double phase lead compensation order; calculate the inverse transformation of the z-domain lead phase compensation error, and substitute it into the double phase lead compensation iterative learning law, and then get System input during the first iteration; load the first and second system input to the manipulator system model to obtain the corresponding system output, and calculate the iterative learning control tracking error, and judge whether the iterative learning control tracking error reaches the allowable precision of the iterative learning control tracking error, if If reached, stop the iteration, otherwise proceed to the next round of iteration. The method of the invention not only improves the transient learning performance of the system, expands the learning bandwidth of the system, but also expands the adjustment range of the ILC learning gain.
Description
technical field [0001] The invention relates to the field of iterative learning control, in particular to a double phase lead compensation iterative learning control method for a manipulator system. Background technique [0002] Iterative Learning Control (ILC) can completely track the ideal output trajectory of the system within a limited time. It was first proposed by Japanese scholar Uchiyana in 1978, and it has been widely used in high-speed and high-precision industrial production practices, such as industrial robots, high-precision CNC machine tools, motor servos, high-precision printers, and integrated circuit manufacturing. [0003] The robot arm is a complex coupling system, and there are couplings of various kinematic joints. At the same time, there are many factors that are difficult to analyze accurately, such as system friction, gear backlash and offset, etc. To solve these problems, traditional PID control and PD control require high-gain control coefficients...
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IPC IPC(8): B25J9/16
CPCB25J9/163
Inventor 傅文渊余志同
Owner HUAQIAO UNIVERSITY