Robust wavelet-neural-network sliding-mode control system for permanent magnet synchronous motor drive

An intelligent sliding-mode speed controller for achieving favourable decoupling control and high-precision speed tracking performance of permanent-magnet synchronous motor (PMSM) drives is proposed. The intelligent controller consists of a sliding-mode controller (SMC) in the feedback loop in addition to an online trained wavelet-neural-network controller (WNNC) connected in parallel with the SMC to construct a robust wavelet-neural-network sliding-mode controller (RWNNSMC). The RWNNSMC controller combines the merits of the SMC with robust characteristics and the WNNC which combines the capability of artificial neural networks for online learning ability and the capability of wavelet decomposition for identification ability. The theoretical analyses of both SMC and WNNC speed controllers are developed. The WNN bound observer is utilised to predict the uncertain system dynamics to relax the requirement of uncertainty bound in the design of SMC. A computer simulation is developed to demonstrate the effectiveness of the proposed intelligent sliding-mode speed controller. An experimental system is established to verify the effectiveness of the proposed control system. All control algorithms are implemented in a TMS320C31 digital signal processor-based control computer. The simulated and experimental results confirm that the proposed RWNNSMC grants robust performance and precise response regardless of load disturbances and PMSM parameter uncertainties.