Title :
Adaptive fuzzy logic control of feedback linearizable discrete-time nonlinear systems
Author_Institution :
Syst. & Control Res., Automated Analysis Corp., Peoria, IL, USA
Abstract :
The objective of this paper is to achieve tracking control of a class of unknown feedback linearizable nonlinear dynamical systems using a discrete-time fuzzy logic controller (FLC). Discrete-time FLC design is significant because almost all FLCs are implemented on digital computers. A repeatable design algorithm and the stability proof for an adaptive fuzzy logic controller is presented, that uses basis functions based on the fuzzy system, unlike most standard adaptive control approaches which generate basis vectors by computing a “regression matrix”. A novel approach to adapt the fuzzy system parameters is attempted. Using this adaptive fuzzy logic controller, with mild assumptions on the class of discrete-time nonlinear systems, the uniform ultimate boundedness of the closed-loop signals is presented. Certainty equivalence is not used and regression matrix not required. The result is a model-free universal fuzzy controller that works for any system in the given class of systems
Keywords :
adaptive control; closed loop systems; control system synthesis; discrete time systems; feedback; fuzzy control; nonlinear dynamical systems; stability; adaptive control; closed-loop signals; discrete-time systems; feedback; fuzzy logic control; linearizable nonlinear dynamical systems; stability; Adaptive control; Algorithm design and analysis; Control systems; Fuzzy logic; Fuzzy systems; Linear feedback control systems; Nonlinear control systems; Nonlinear dynamical systems; Programmable control; Stability;
Conference_Titel :
Intelligent Control, 1996., Proceedings of the 1996 IEEE International Symposium on
Conference_Location :
Dearborn, MI
Print_ISBN :
0-7803-2978-3
DOI :
10.1109/ISIC.1996.556190