Adaptive neural control using fuzzy adaptive parameter for nonlinear processes

Abstract

This paper presents an alternative fuzzy adaptive parameter for a neural emulator applied to an indirect adaptive control of nonlinear processes. A fuzzy supervisor is presented. It does not need to initialize any term. Avoiding the effort to find an optimal choice of neural emulator adaptive parameter, using a fuzzy adaptive parameter denotes the most important advantage. The simulation results and comparisons are provided to show the effectiveness and the validity of the neural controller based on fuzzy emulator. The satisfactory results prove the efficiency of the proposed approach in terms of neural control of nonlinear processes.