Adaptive iterative learning control for permanent magnet synchronous motor servo system
ZHU Guo-xin
LEI Ming-kai
ZHAO Xi-mei
Abstract：Aiming at the problem that the tracking accuracy reduces and the error is divergent due to such uncertain factors as parameter perturbation and stochastic disturbance in the process of performing repetitive tasks for permanent magnet synchronous motor ( PMSM ) servo system, an adaptive iterative learning control ( AILC) method was proposed. Based on the PD feedback control, an adaptive iterative term was added to perform the iterative learning of unknown parameters in the control law to reduce the effect of uncertain factors on the system performance. Both system model with the uncertain disturbance and PMSM adaptive iterative learning control system were established, and the convergence of the scheme was analyzed based on Lyapunov stability theory. The results demonstrate that compared with conventional PD type ILC, the proposed method has faster convergence rate and higher tracking accuracy, and can effectively improve the system performance.
Keywords：permanent magnet synchronous motor ( PMSM )iterative learning control ( ILC )adaptive iterative learning control ( AILC)feedback controlparameter perturbationtracking errorconvergence rateservo system
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：6( 6-11 )