Segmentation filtering iterative learning control method of motor servo system

Abstract

Provided is a segmentation filtering iterative learning control method of a motor servo system. The method comprises steps of firstly determining learning law convergence frequency domain scope is 0-f<c0> when a zero-phase filter, i.e., Q(z)=1, is not introduced; then performing reference trajectory track of the primary iteration-free loop so as to obtain an error signal e0(t), applying the EMD algorithm to decompose the e0(t) into limited number of intrinsic mode functions, and obtaining time sequence characteristics of the error signal e0(t) via the Hilbert conversion; then using frequency f<c0> as the segmentation reference frequency; segmenting the error signal e0(t), and distinguishing time segments where instant frequency of the error signal e0(t) is higher than the f<c0> and lower than the f<c0>; designing cut-off frequency of a zero phase according to the Hilbert time sequence characteristics of the e0(t); in the time segment where the instant frequency of the error signal is higher than the f<c0>, f<c>=f<c0>+1 / 2(f<max>-f<c0>) is adopted as the cut-off frequency of the filter, wherein fmax represents the highest frequency in this segment; in other time segments, f<c0> is adopted as the cut-off frequency of the filter; and at last, applying the designed segmentation zero phase filter to the following iterative learning control processes.

Description

(1) Technical field [0001] The invention belongs to an iterative learning control method applied to a motor servo system. (2) Background technology [0002] Iterative Learning Control (ILC) uses the control experience and deviation information of previous batches of the control system to improve the control performance of the current batch and achieve precise tracking of the desired trajectory. It provides an effective control method for the motor servo system and its application equipment (such as industrial robots, CNC machine tools, etc.) with high-speed and high-precision requirements. [0003] The basic idea of ​​ILC appeared in a Japanese research paper published by Japanese scholar Uchiyama in 1978. Until 1984, Arimoto and others perfected the basic idea of ​​iterative learning, established a practical algorithm, and gradually formed the theory of iterative learning control. In the actual application of ILC, due to the existence of difficult-to-identify parasitic vi...

AI Technical Summary

Problems solved by technology

[0005] The present invention overcomes the disadvantage of poor learning transient in the prior art, and provides a segmented filter iterative learning control method for the motor servo system to improve the learning transient of the ILC system and improve tracking accuracy

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