Fuzzy gain scheduling controllers based on fuzzy models

Author

Zhao, Jun ; Wertz, Vincent ; Gorez, Raymond

Author_Institution

Centre for Syst. Eng. & Appl. Mech., Univ. Catholique de Louvain, Belgium

Volume

3

fYear

1996

fDate

8-11 Sep 1996

Firstpage

1670

Abstract

Takagi-Sugeno fuzzy models provide an effective representation of complex nonlinear systems in terms of fuzzy sets and fuzzy reasoning applied to a set of linear input-output submodels. Based on such models, fuzzy gain scheduling controllers can be sought by means of linear matrix inequality (LMI) methods. This systematic model-based synthesis technique results in fuzzy control systems with guaranteed stability and robustness. Moreover, some particular design requirements considering implementation of fuzzy controllers are also discussed in this paper

Keywords

control system synthesis; fuzzy control; large-scale systems; matrix algebra; nonlinear control systems; robust control; Takagi-Sugeno fuzzy models; complex nonlinear systems; design requirements; fuzzy gain scheduling controllers; fuzzy reasoning; fuzzy sets; linear input-output submodels; linear matrix inequality methods; model-based synthesis technique; Control system synthesis; Fuzzy control; Fuzzy reasoning; Fuzzy sets; Fuzzy systems; Linear matrix inequalities; Nonlinear systems; Robust control; Robust stability; Takagi-Sugeno model;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on

Conference_Location

New Orleans, LA

Print_ISBN

0-7803-3645-3

Type

conf

DOI

10.1109/FUZZY.1996.552621

Filename

552621