Browse > Article
http://dx.doi.org/10.5302/J.ICROS.2006.12.3.227

Intelligent Digital Redesign of a Fuzzy-Model-Based Controllers for Nonlinear Systems with Uncertainties  

Jang Kwon-Kyu (군산대학교 전자정보공학부)
Kwon Oh-Shin (군산대학교 전자정보공학부)
Joo Young-Hoon (군산대학교 전자정보공학부)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.12, no.3, 2006 , pp. 227-232 More about this Journal
Abstract
In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear system which may also contain system uncertainties. The continuous-time uncertain TS fuzzy model is first contructed to represent the uncertain nonlinear system. A parallel distributed compensation(PDC) technique is then used to design a fuzzy-model-based controller for both stabilization. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using a globally intelligent digital redesign method. This new technique is designed by a global matching of state variables between analog control system and digital control system. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear systems with uncertainties. Finally, Chaotic Lorenz system is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.
Keywords
intelligent degital redesign; fuzzy-model-based controller; LMI; PDC; TS fuzzy; nonlinear system; uncertainty;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
1 Y. H. Joo, G. Chen, and L. S. Shieh, 'Hybrid state-space fuzzy model-based controller with dual-rate sampling for digital control of chaotic systems,' IEEE Transactions on Fuzzy Systems, vol. 7, pp. 394-408, Aug. 1999   DOI   ScienceOn
2 J. Li, D. Niemann and H. O. Wang, 'Parallel distributed compensation for Takagi-Sugeno fuzzy models: multi-objective controller design,' Proc. of ACC, pp. 1832-1836, San Diego, California, June, 1999   DOI
3 K. Tanaka and M. Sugeno, 'Stability analysis and design of fuzzy control systems,' Fuzzy Sets and Systems, vol. 45, no. 2, pp. 134-156, 1992   DOI   ScienceOn
4 K. L. Cho, Y. H. Joo and J. B. Park, 'Intelligent Digital Redesign for Dynamical Systems with Uncertainties,' 퍼지 및 지능시스템학회 논문지, 2003, vol. 13, no 6, pp. 667-672   과학기술학회마을   DOI
5 T. Takagi and M. Sugeno, 'Fuzzy identification of systems and its applications to modeling and control,' IEEE Transactions on Fuzzy Systems, vol. 15, pp. 116-132, 1985
6 H. O. Wang, K. Tanaka, and M. Griffin, 'An approach of fuzzy control of nonlinear systems: stability and design issues,' IEEE Transactions on Fuzzy Systems, vol. 4, pp. 14-23, Feb. 1996   DOI   ScienceOn
7 K. Tanaka, T. Ikeda, and H. O. Wang, 'Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, $H_{\infty}$, control theory, and linear matrix inequalities,' IEEE Transactions on Fuzzy systems, vol. 86, no. 3, pp. 279-288, 1997
8 H. J. Lee, J. B. Park, and G. Chen, 'Robust fuzzy control of nonlinear systems with parametric uncertainties,' IEEE Transactions on Fuzzy Systems, 2000. (to be published)   DOI   ScienceOn
9 W. Chang, Y. H. Joo, J. B. Park, 'Digital control of an inverted pendulum by using ingelligent digital redisign' 대한전기학회 논문지, vol. 50D, pp. 457-463, 2001, 10
10 Y. H. Joo, Y. W. Lee, D. B. Cha, and J. H. Oh, Intelligent Digitally Redesigned Fuzzy Controller,' Int. Journal of Fuzzy logic and Intelligent Systems, vol. 2, no. 3, pp. 221-226, 2002, 12