State observer based robust adaptive fuzzy controller for nonlinear uncertain and perturbed systems

Authors:
A. Hamzaoui;N. Essounbouli;K. Benmahammed;J. Zaytoon
Affiliations:
Lab. d'Automatique et de Microelectronique-UFR Sci. Exactes et, Univ. of Reims Champagne-Ardenne, France;-;-;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2004

Citing 0
Cited 8

Robust H∞ fuzzy static output feedback control of T-S fuzzy systems with parametric uncertainties

Fuzzy Sets and Systems
Robust H∞ fuzzy control of nonlinear systems with multiple time delays

International Journal of Systems Science
How to design a fuzzy adaptive controller based on observers for uncertain affine nonlinear systems

Fuzzy Sets and Systems
Intelligent adaptive control for MIMO uncertain nonlinear systems

Expert Systems with Applications: An International Journal
Adaptive fuzzy output tracking control for a class of uncertain nonlinear systems

Fuzzy Sets and Systems
State observer-based adaptive fuzzy output-feedback control for a class of uncertain nonlinear systems

Information Sciences: an International Journal
Fire-rule-based direct adaptive type-2 fuzzy H∞ tracking control

Engineering Applications of Artificial Intelligence
Composite adaptive fuzzy H∞ tracking control of uncertain nonlinear systems

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

A robust adaptive fuzzy controller, based on a state observer, for a nonlinear uncertain and perturbed system is presented. The state observer is introduced to resolve the problem of the unavailability of the state variables. Two control signals are added to a basic state feedback control law, deduced from a nominal model, to guarantee the tracking performance in the presence of structural uncertainties and external disturbances. The first control signal is computed from an adaptive fuzzy system and eliminates the effect of structural uncertainties and estimation errors. Updating the adjustable parameters is ensured by a PID law to obtain a fast convergence. Robustness of the closed-loop system is guaranteed by an H∞ supervisor computed from a Riccati type equation. Simulation example is presented to show the efficiency of the proposed method.