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ROBUST DIRECT ADAPTIVE CONTROLLER FOR A CLASS OF NONLINEAR SYSTEMS BASED ON NEURAL NETWORKS AND FUZZY LOGIC SYSTEMS

MOHAMED CHEMACHEMA

Laboratoire d'automatique et de robotique, University of Constantine, route de Ain el Bey, 25000 Constantine, Algeria

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and

KHALED BELARBI

Laboratoire d'automatique et de robotique, University of Constantine, route de Ain el Bey, 25000 Constantine, Algeria

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https://doi.org/10.1142/S0218213007003412Cited by:18 (Source: Crossref)

Abstract

In this paper a direct adaptive control algorithm based on a neural network NN as controller and a fuzzy inference system FIS as control error estimator is presented for a class of SISO uncertain nonlinear systems. The weights adaptation laws are based on the control error. A fuzzy inference system is used to provide an estimate of this error based on past history of the system behavior. The stability of the closed loop is studied using Lyapunov theory. Simulation results demonstrate the effectiveness of the proposed approach.

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