Title :
Control of Takagi-Sugeno fuzzy systems via feedback linearization
Author_Institution :
Dept. of Physiol. & Biophys., Texas Univ., Galveston, TX, USA
Abstract :
Takagi-Sugeno (TS) fuzzy modeling technique, a black-box discrete-time approach for system identification, has widely been used to model behaviors of complex dynamic systems. We first prove that a class of TS fuzzy systems is nonlinear time-varying ARX (Auto-Regressive with the Extra input). We then develop a feedback linearization technique for systematically designing an output tracking controller so that output of a controlled TS fuzzy system achieves perfect tracking of any bounded time-varying trajectory
Keywords :
control system synthesis; discrete time systems; feedback; fuzzy control; fuzzy systems; identification; linearisation techniques; nonlinear control systems; time-varying systems; Auto-Regressive with the Extra input; TS fuzzy systems; Takagi-Sugeno fuzzy systems; black-box discrete-time approach; complex dynamic systems; feedback linearization; fuzzy control; fuzzy modeling technique; nonlinear time-varying ARX; output tracking controller design; system identification; time-varying trajectory tracking; Control systems; Fuzzy systems; Linear feedback control systems; Linearization techniques; Nonlinear dynamical systems; Output feedback; System identification; Takagi-Sugeno model; Time varying systems; Trajectory;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.633088
