Robust Optimal Control of High-Speed Permanent-Magnet Synchronous Motor Drives via Self-Constructing Fuzzy Wavelet Neural Network

Abstract

This paper proposes a robust optimal control (ROC) scheme with self-constructing fuzzy wavelet neural network (SCFWNN) to achieve high dynamic performance for high-speed permanent-magnet synchronous motor (HSPMSM) drive system. The proposed ROC scheme combines an adaptive controller via backstepping technique, a SCFWNN uncertainty identifier, a robust controller and an optimal controller. First, an optimal backstepping controller (OBC) is developed according to Lyapunov stability analysis and optimal control theory. In order to relax the requirement for the lumped parameter uncertainties in the OBC law, the design of a SCFWNN uncertainty identifier for the online approximation of nonlinear uncertainties is developed. Further, a robust controller is designed to recover the residual of the SCFWNN approximation errors. In addition, the online adaptive control laws are derived on the basis of Lyapunov stability analysis and optimal control technique, so that the stability of the ROC can be guaranteed. The simulation results are presented to verify the effectiveness of the proposed ROC scheme. From the simulation results, it can be inferred that the proposed ROC scheme with SCRFWNN uncertainty identifier can achieve favorable tracking performance irrespective of the presence of compounded disturbances and parameter uncertainties.