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ADAPTIVE-LEARNING CONTROL FOR PERMANENT-MAGNET LINEAR SYNCHRONOUS MOTORS

SONG Yi-xu,WANG Chun-hong,YIN Wen-sheng,JIA Pei-fa(Tsinghua University,Haidian District,Beijing 100084,China)  
There is more complexity in controller design for Permanent-magnet linear synchronous motors (PMLSM) due to the elimination of mechanical transmission mechanisms.Firstly,PMLSM are more sensitive to disturbances and parameters uncertainties.Furthermore,significant nonlinear effects (e.g.thrust ripple) worsen its motion precision.In order to resolve above-mentioned issues,an adaptive-learning control scheme was applied to improve trajectory tracking performance of PMLSM.Convergence analysis of the algorithm was given in both repetitive operational mode and single operational mode.The control scheme was verified in experiments.The scheme is based on iterative learning control.The controller consists of two terms,the adaptive-learning term compensates nonlinear effects of the system in the repetitive tasks,and another term enhances robustness to guarantee stability in the single operational mode.The experimental results show that tracking precision of PMLSM can be effectively improved by the scheme.
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