Design and stability analysis of fuzzy model-based nonlinear controller for nonlinear systems using genetic algorithm

This paper presents stability analysis of fuzzy model-based nonlinear control systems, and the design of nonlinear gains and feedback gains of the nonlinear controller using a genetic algorithm (GA) with arithmetic crossover and nonuniform mutation. A stability condition is derived based on Lyapunov's stability theory with a smaller number of Lyapunov conditions. A solution of the stability conditions is also determined using GA. An application example of stabilizing a cart-pole typed inverted pendulum system is given to show the stabilizability of the nonlinear controller.

[1]  F.H.F. Leung,et al.  Tuning of the structure and parameters of neural network using an improved genetic algorithm , 2001, IECON'01. 27th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.37243).

[2]  Rainer Palm,et al.  Stability of fuzzy gain-schedulers: sliding-mode based analysis , 1997, Proceedings of 6th International Fuzzy Systems Conference.

[3]  H. Lam,et al.  A switching controller for uncertain nonlinear systems , 2002 .

[4]  Hak-Keung Lam,et al.  Linear controllers for fuzzy systems subject to unknown parameters: stability analysis and design based on linear matrix inequality (LMI) approach , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[5]  Euntai Kim,et al.  Numerical stability analysis of fuzzy control systems via quadratic programming and linear matrix inequalities , 1999, IEEE Trans. Syst. Man Cybern. Part A.

[6]  Kazuo Tanaka,et al.  An approach to fuzzy control of nonlinear systems: stability and design issues , 1996, IEEE Trans. Fuzzy Syst..

[7]  L. P. Holmblad,et al.  Control of a Cement Kiln by Fuzzy Logic Techniques , 1981 .

[8]  H. Lam,et al.  Design of fuzzy controllers for uncertain nonlinear systems using stability and robustness analyses , 1998 .

[9]  Kazuo Tanaka,et al.  Backing control problem of a mobile robot with multiple trailers: fuzzy modeling and LMI-based design , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[10]  Hak-Keung Lam,et al.  Optimal and stable fuzzy controllers for nonlinear systems subject to parameter uncertainties using genetic algorithm , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[11]  M. B. Beck,et al.  Fuzzy control of the activated sludge wastewater treatment process , 1980, Autom..

[12]  S. Okuma,et al.  Accelerated evolutionary computation using fitness estimation , 1999, IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028).

[13]  Kazuo Tanaka,et al.  Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, H∞ control theory, and linear matrix inequalities , 1996, IEEE Trans. Fuzzy Syst..

[14]  Kazuo Tanaka,et al.  A unified approach to controlling chaos via an LMI-based fuzzy control system design , 1998 .

[15]  Hak-Keung Lam,et al.  Fuzzy control of a class of multivariable nonlinear systems subject to parameter uncertainties: model reference approach , 2001, Int. J. Approx. Reason..

[16]  E. Yaz Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.

[17]  Hak-Keung Lam,et al.  Nonlinear state feedback controller for nonlinear systems: Stability analysis and design based on fuzzy plant model , 2001, IEEE Trans. Fuzzy Syst..

[18]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[19]  Gang Feng,et al.  Analysis and design for a class of complex control systems Part I: Fuzzy modelling and identification , 1997, Autom..

[20]  Hak-Keung Lam,et al.  Tuning of the structure and parameters of a neural network using an improved genetic algorithm , 2003, IEEE Trans. Neural Networks.

[21]  S. Amin,et al.  Dynamic local search , 1997 .

[22]  Gang Feng,et al.  Analysis and design for a class of complex control systems part II: Fuzzy controller design , 1997, Autom..

[23]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[24]  Hak-Keung Lam,et al.  A neural fuzzy network with optimal number of rules for short-term load forecasting in an intelligent home , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[25]  Hak-Keung Lam,et al.  Stable and robust fuzzy control for uncertain nonlinear systems , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[26]  Hak-Keung Lam,et al.  On design of a switching controller for nonlinear systems with unknown parameters based on a model reference approach , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

[27]  Farid Sheikholeslam,et al.  Stability analysis and design of fuzzy control systems , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

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

[29]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[30]  Hak-Keung Lam,et al.  On interpretation of graffiti commands for eBooks using a neural network and an improved genetic algorithm , 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).