Feedback linearization of nonlinear systems using fuzzy logic

Article type: Research Article

Authors: Jagannathan, S.^; | Lewis, F.L.

Affiliations: Department of Electrical Engineering, the University of Texas at San Antonio, 6900 North Loop 1604 West, San Antonio, TX 78249–0665, USA | Automation and Robotics Research Institute, The University of Texas at Arlington,7300 Jack Newell Blvd. S, Ft. Worth, TX 76118, USA

Note: [] Corresponding author. E-mail: [email protected].

Abstract: The objective of this paper is to achieve tracking control of a class of unknown nonlinear dynamical systems using a fuzzy logic controller (FLC). A repeatable design algorithm and stability proof is examined for an adaptive fuzzy logic controller that uses basis vectors based on the fuzzy system, unlike most standard adaptive control approaches which use basis vectors depending on the unknown plant (e.g. a tediously computed “regression matrix”). A �-modification approach to adapt the fuzzy system parameters is investigated. With mild assumptions on the state-feedback linearizable nonlinear systems, using this adaptive fuzzy logic controller the uniform ultimate boundedness of the closed-loop signals is presented and that the controller achieves tracking. In fact, the fuzzy system designed is a model-free universal fuzzy controller that can be applied for any system in the given class of systems.

Journal: Journal of Intelligent and Fuzzy Systems, vol. 7, no. 2, pp. 107-124, 1999