Fuzzy neural network sliding-mode position controller for induction servo motor drive

A sliding-mode controller with an integral-operation switching surface is a dopted to control the position of an induction servo motor drive. Moreover, to relax the requirement for the bound of uncertainties, a fuzzy neural ne twork (FNN) sliding-mode controller is investigated, in which the FNN is ut ilised to estimate the bound of uncertainties real-time. The theoretical an alyses for the proposed FNN sliding-mode controller are described in detail . In addition, to guarantee the convergence of tracking error, analytical m ethods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the FNN. Simulation and experimental results show that the proposed FNN sliding-mode controller provides high-performanc e dynamic characteristics and is robust with regard to plant parameter vari ations and external load disturbance. Furthermore, comparing with the slidi ng-mode controller, smaller control effort results, and the chattering phen omenon is much reduced by the proposed FNN sliding-mode controller.