Fuzzy adaptive approach to nonlinear systems control

We consider a direct fuzzy adaptive control of continuous-time nonlinear systems. The proposed adaptive scheme uses a Takagi-Sugeno (TS) fuzzy controller, which allows the inclusion of a priori information in terms of qualitative knowledge about the plant operating points or analytical conventional regulators for those operating points. The closed loop dynamic is proven to be asymptotically stable, and robust against external disturbance and approximation error. The proposed approach performance is evaluated on an induction motor control problem.

[1]  J. Buckley.  Sugeno type controllers are universal controllers , 1993 .

[2]  N. Golea,et al.  Iterative Construction and Optimization of Fuzzy Models , 1999 .

[3]  Stephen Yurkovich,et al.  Fuzzy Control , 1997 .

[4]  ChenBor-Sen,et al.  H tracking design of uncertain nonlinear SISO systems , 1996 .

[5]  Chun-Yi Su,et al.  Adaptive control of a class of nonlinear systems with fuzzy logic , 1994, Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference.

[6]  Kurt Fischle,et al.  An improved stable adaptive fuzzy control method , 1999, IEEE Trans. Fuzzy Syst..

[7]  Hao Ying,et al.  Sufficient conditions on general fuzzy systems as function approximators , 1994, Autom..

[8]  A. Golea,et al.  Fuzzy adaptive control: a hyperstability approach , 2000, ICECS 2000. 7th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.00EX445).

[9]  Bor-Sen Chen,et al.  H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach , 1996, IEEE Trans. Fuzzy Syst..

[10]  Li-Xin Wang,et al.  Adaptive fuzzy systems and control - design and stability analysis , 1994 .

[11]  Kevin M. Passino,et al.  Stable adaptive control using fuzzy systems and neural networks , 1996, IEEE Trans. Fuzzy Syst..

[12]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.