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Iterative learning control using wavelet approximation for permanent magnet linear synchronous motor

Iterative learning control (ILC) algorithm using wavelet approximation is adopted to improve trajectory-tracking performance of permanent magnet linear synchronous motors (PMLSM). The algorithm approximates the unknown nonlinearities of PMLSM by wavelet transform whose approximated coefficients are iteratively adjusted by learning. The sliding mode variable structure control strategy with dead zone is adopted to ensure the robust convergence. The simulation results show that errors between the actual and optimal wavelet coefficients are monotonically decreased with iterations. The proposed scheme overcomes the influences of detent force of PMLSM.