Nonlinear discrete-time controller based on fuzzy-rule emulated network and shuttering condition

Abstract

This article introduces the adaptive controller for a class of nonlinear discrete-time systems based on the sliding shuttering condition and the self adjustable network called Multi-Input Fuzzy Rules Emulated Network (MIFREN). By using only the online learning phase, MIFREN's functional is the nonlinear discrete-tine function approximation and the disturbance estimation together. The proposed theorem is introduced for the designing procedure of all controller's parameters and MIFREN's adaptation gain. Simulation results demonstrate the justification of the theorem for the tracking performance and the unknown disturbance rejection.