title: Identification of uncertain nonlinear systems for robust fuzzy control.
abstract: In this paper, we consider fuzzy identification of uncertain nonlinear systems in Takagi-Sugeno (T-S) form for the purpose of robust fuzzy control design. The uncertain nonlinear system is represented using a fuzzy function having constant matrices and time varying uncertain matrices that describe the nominal model and the uncertainty in the nonlinear system respectively. The suggested method is based on linear programming approach and it comprises the identification of the nominal model and the bounds of the uncertain matrices and then expressing the uncertain matrices into uncertain norm bounded matrices accompanied by constant matrices. It has been observed that our method yields less conservative results than the other existing method proposed by Skrjanc et al. (2005). With the obtained fuzzy model, we showed the robust stability condition which provides a basis for different robust fuzzy control design. Finally, different simulation examples are presented for identification and control of uncertain nonlinear systems to illustrate the utility of our proposed identification method for robust fuzzy control.
authors.affiliation: Department of Electronics and Communication Engineering, Indian Institute of Technology, Guwahati, Guwahati-781039, Assam, India. d.senthil@iitg.ernet.in
authors.forename: D
authors.initials: D
authors.lastname: Senthilkumar
authors.forename: Chitralekha
authors.initials: C
authors.lastname: Mahanta
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003627:Data Interpretation, Statistical; D004581:Electronics; D017143:Fuzzy Logic; D017711:Nonlinear Dynamics; D035501:Uncertainty