Browse > Article

Robust Stability Analysis and Design of Fuzzy Model Based Feedback Linearization Control Systems  

박창우 (전자부품연구원)
이종배 (전자부품연구)
김영욱 (전자부품연구)
성하경 (전자부품연구원)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.41, no.3, 2004 , pp. 79-90 More about this Journal
Abstract
Systematical robust stability analysis and design scheme for the feedback linearization control systems via fuzzy modeling are proposed. It is considered that uncertainty and disturbances are included in the Takagi-Sugeno fuzzy models representing the nonlinear plants. Robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions and by converting the analysis and design problems into the linear matrix inequality optimization, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.
Keywords
Fuzzy modeling; feedback linearization control; linear matrix inequalities; Takagi-Sugeno model;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Kim, E., Kang, H. J., and Park, M., Numerical stability analysis of fuzzy control systems via quadratic programming and linear matrix inequalities, IEEE Trans. Fuzzy Systems, 1999, 29(4) pp.333-346   DOI   ScienceOn
2 Vidyasagar, M., Nonlinear system analysis, Prentice-Hall, Englewood Cliffs, 1993
3 Gahinet, P., Nemirovski, A., Laub, A., and Chilali, M., LMI Control Toolbox, The MathWorks Inc., Natick, 1995
4 Kim, E. and Kim, D., Stability analysis and synthesis for an affair fuzzy system via LMI and ILMI: discreate case, IEEE Trans. Syst. Man and Cybernetics, 2001, 31(1) pp.132-140   DOI   ScienceOn
5 Boyd, S., Linear matrix inequalities in systems and control theory, SIAM, Philadelphia, 1994
6 Fischle, K. and Schroder, D., An improved stable adaptive fuzzy control method, IEEE Trans. Fuzzy Systems, 1999, 7(1) pp.27-40   DOI   ScienceOn
7 Takagi, T., Sugeno, M., Fuzzy Identification of systems and its application to modeling and control, IEEE Trans. Syst., Man, Cybern. 1985, 15(1) pp.116-132   DOI   ScienceOn
8 Sugeno, M., Fuzzy control, Nikangoubyou-Shinnbun-sha, Tokyo, 1988
9 Y.-W. Cho, C.-W. Park, J.-H. Kim, M. Park, 'Indirect model reference adaptive fuzzy control of dynamic fuzzy state space model', IEE Proc. Control Theory Appl., vol. 148, No. 4, July, 2001   DOI   ScienceOn
10 Tsay, D. L. Chung, H. Y. and Lee, C. J., The adaptive control of nonlinear systems using the Sugeno-type of fuzzy logic, IEEE Trans. Fuzzy Systems, 1999, 7(2) pp.225-229   DOI   ScienceOn
11 Fuh, C. C., Tung, P. C., Robust stability analysis of fuzzy control systems, Fuzzy Sets and Systems, 1997, 88(3) pp.289-298   DOI   ScienceOn
12 Tanaka, K., Ikeda, T., Wang, H. O., Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, $H^{\infty}$ control theory, and linear matrix inequalities, IEEE Trans. Fuzzy Systems, 1996, 4(1) pp.1-13   DOI   ScienceOn
13 Kang, H. J., Kwon, C., Lee, C. H. and Park, M. Robust stability analysis and design method for the fuzzy feedback linearization regulator, IEEE Trans. Fuzzy Systems, 1998, 6(4) pp.464-472   DOI   ScienceOn
14 Park, C. W., Kang, H. Y., Yee, Y. H. and Park, M. Numerical robust stablity analysis of fuzzy feedback linearization regulator based on linear matrix ineuqality approach, IEE Proc-Control Theory Appl., in press
15 Nesterov, Y., Nemirovsky, A., Interior-point poly nomial methods in convex programming, SIAM, Philadelphia, 1994
16 Wang, H. O., Tanaka, K., Grifin, F. G., An approach to fuzzy control of nonlinear system: stability and design issues, IEEE Trans. Fuzzy Systems, 1996, 4(1), pp.14-23   DOI   ScienceOn