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Direct and Indirect Robust Adaptive Fuzzy Controllers for a Class of Nonlinear Systems

Abstract : In this paper, we propose direct and indirect adaptive fuzzy sliding mode control approaches for a class of nonaffine nonlinear systems. In the direct case, we use the implicit function theory to prove the existence of an ideal implicit feedback linearization controller, and hence approximate it to attain the desired performances. In the indirect case, we exploit the linear structure of a Takagi-Sugeno fuzzy system with constant conclusion to establish an affine-in-control model, and therefore design an indirect adaptive fuzzy controller. In both cases, the adaptation laws of the adjustable parameters are deduced from the stability analysis, in the sense of Lyapunov, to get a more accurate approximation level. In addition to their robustness, the design of the proposed approaches does not require the upper bounds of both external disturbances and approximation errors. To show the efficiency of the proposed controllers, a simulation example is presented.
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Contributor : Najib Essounbouli Connect in order to contact the contributor
Submitted on : Saturday, July 24, 2021 - 2:28:13 AM
Last modification on : Thursday, October 14, 2021 - 1:10:07 PM
Long-term archiving on: : Monday, October 25, 2021 - 6:02:35 PM


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  • HAL Id : hal-03298770, version 1



Najib Essounbouli, Abdelaziz Hamzaoui. Direct and Indirect Robust Adaptive Fuzzy Controllers for a Class of Nonlinear Systems. International Journal of Control, Automation, and Systems, Springer, 2006, 4 (2). ⟨hal-03298770⟩



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