A New Model Reference Adaptive Control of PMSM Using Neural Network Generalized Inverse

Abstract

Abstract.A new strategy of model reference adaptive control (MRAC) system based on neural network generalized inverse (NNGI) algorithm, termed as MRAC-NNGI system, is proposed for the current and speed regulations of permanent magnet synchronous motor (PMSM) drives. Due to the fact that PMSM is a multivariable nonlinear system with strong couplings, this paper gives an analysis of generalized reversibility combined with NN. The developed scheme of NNGI is transformed into a pseudo-linear system from connecting the motor plant and achieved the purposes of decoupling and linearization with Levenberg-Marquardt algorithm off-line. Therefore, an adjustable gain of closed-loop adaptive controller is developed by introducing MRAC into this kind of pseudo-linear system. The self-adaptive law is given for the gain regulation of linear system. Comparison of simulation results from others widely used algorithms confirm that it incorporates the merits of model-free learning, highprecision tracking and strong anti-interference capability.