A New Method For Linguistic Modeling With Stability Analysis And Applications

Abstract This paper presents a new approach for linguistic system modeling which is also suitable for stability analysis of linguistic models. First we present an approach, which is called infinite place model, described using modified fuzzy Petri net, with uses a new place definition based on physical infinity state concept. This method has some practical difficulties, which are taking care of in the second approach called variation model. This paper presents the above methodologies with some definitions and a necessary and sufficient condition for stability of a class of linguistic fuzzy system. This stability analysis is verified using some benchmark systems simulations.

[1]  Bahram Shafai,et al.  Qualitative robust fuzzy control with applications to 1992 ACC benchmark , 1999, IEEE Trans. Fuzzy Syst..

[2]  Jerry M. Mendel,et al.  Generating fuzzy rules by learning from examples , 1992, IEEE Trans. Syst. Man Cybern..

[3]  Stefan Preitl,et al.  Center Manifold Theory Approach to the Stability Analysis of Fuzzy Control Systems , 1999, Fuzzy Days.

[4]  Witold Pedrycz,et al.  A stability analysis of fuzzy control system using a generalized fuzzy Petri net model , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[5]  Mehrdad Nouri Khajavi,et al.  Fuzzy adaptive robust optimal controller to increase load following capability of nuclear reactors , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[6]  S.K.Y. Nikravesh,et al.  Two new approaches for linguistic fuzzy modeling and introduction to their stability analysis , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[7]  S. Farinwata A robust stabilizing controller for a class of fuzzy systems , 1999, Proceedings of the 38th IEEE Conference on Decision and Control (Cat. No.99CH36304).

[8]  P. Albertos,et al.  Control Engineering Solutions: A Practical Approach , 1996 .

[9]  Takeshi Furuhashi,et al.  A new sufficient condition for stable fuzzy control system and its design method , 2001, IEEE Trans. Fuzzy Syst..

[10]  Yoshiki Uchikawa,et al.  Stability analysis of fuzzy control systems using Petri nets , 1996, Proceedings of North American Fuzzy Information Processing.

[11]  Witold Pedrycz,et al.  A generalized fuzzy Petri net model , 1994, IEEE Trans. Fuzzy Syst..

[12]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[13]  Kazuo Tanaka,et al.  An LMI approach to fuzzy controller designs based on relaxed stability conditions , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[14]  Euntai Kim A new approach to numerical stability analysis of fuzzy control systems , 2001, IEEE Trans. Syst. Man Cybern. Syst..

[15]  Michio Sugeno,et al.  On stability of fuzzy systems expressed by fuzzy rules with singleton consequents , 1999, IEEE Trans. Fuzzy Syst..

[16]  Mohammad Bagher Menhaj,et al.  A modified dynamic non-singleton fuzzy logic system for nonlinear modeling , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[17]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..