Optimal state-feedback control of time-varying TS-fuzzy-model-based systems by using an integrative computational approach

International Journal of Innovative Computing, Information and Control

Volumn 3, Issue 4, 2007, Pages 873-885

  Ho, Wen Hsien ^a   Tsai, Jinn Tsong ^b   Liu, Tung Kuan ^c   Chou, Jyh Horng ^c  

^a KAOHSIUNG MEDICAL UNIVERSITY   (Taiwan)

^b NATIONAL PINGTUNG UNIVERSITY   (Taiwan)

^c NATIONAL KAOHSIUNG UNIVERSITY OF APPLIED SCIENCES   (Taiwan)

Author keywords

Hybrid Taguchi genetic algorithm; Legendre series approach; Quadratic hnite horizon optimal control; Time varying state feedback controller; Time varying Takagi Sugeno fuzzy model

Indexed keywords

EID: 63649144053     PISSN: 13494198     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (20)

1. Takagi, T. and M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Trans. on Systems, Man and Cybernetics, vol.15, pp.116-132, 1985.
2. Babuska, R., Fuzzy Modeling for Control, Kluwer, Boston, 1998.
3. Farinwata, S. S., D. Filev and R. Langari, Fuzzy Control: Synthesis and Analysis, John Wiley and Sons, Chichester, 2000.
4. Tanaka, K. and H. O. Wang, Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach, John Wiley and Sons, New York, 2001.
5. Tong, S. C, T. Wang, Y. P. Wang and J. T. Tang, Design and Stability Analysis of Fuzzy Control Systems, Science Press, Beijing, 2004.
6. Shimizu, Y., M. Miyazaki, H. H. Lee and K. Akizuki, Chaos synchronization based on fuzzy model using sliding mode control, Int. J. of Innovative Computing, Information and Control, vol.l, no.3, pp.563-579, 2005.
7. Sun, J., K. Fujimoto, C. Dou, J. Zhong and S. Yuan, H-infinity fuzzy tracking control for multimachine interconnected power system with model uncertainties, Int. J. of Innovative Computing, Information and Control, vol.2, no.l, pp. 61-68, 2006.
8. Benzaouia, A., A. E. Hajjaji and M. Naib, Stabilization of a class of constrained fuzzy systems: A positive invariance approach, Int. J. of Innovative Computing, Information and Control, vol.2, no.4, pp.749-760, 2006.
9. Goodwin, G. C., S. F. Graebe and M. E. Salgado, Control System Design, Prentice-Hall, New Jersey, 2001.
10. Zheng, K., J. M. Xu and L. Yu, Takagi-Sugeno model-based optimal guaranteed cost fuzzy control for inverted pendulums, Control Theory and Applications, vol.21, pp.703-708, 2004.
11. Li, D. Q., Optimal fuzzy guaranteed cost control for delta-operator based nonlinear systems, Systems Engineering and Electronics, vol.27, pp. 883-888, 2005.
12. Ovaska, S. J., Computationally Intelligent Hybrid Systems: The Fusion of Soft Computing and Hard Computing, IEEE Press, New Jersey, 2005.
13. Chou, J. H., W. H. Liao and J. J. Li, Application of Taguchi-genetic method to design optimal greyfuzzy controller of a constant turning force systems, Proc. of the 15th CSME Annual Conference, Tainan, Taiwan, pp.31-38, 1998.
14. Tsai, J. T., T. K. Liu and J. H. Chou, Hybrid Taguchi-genetic algorithm for global numerical optimization, IEEE Trans. on Evolutionary Computation, vol.8, pp. 365-377, 2004.
15. Chou, J. H., Application of Legendre series to the optimal control of integrodifferential equations, Int. J. of Control, vol.45, pp.269-277, 1987.
16. Barnett, S., Matrix Methods for Engineers and Scientists, McGraw-Hill, New York, 1979.
17. Gen, M. and R. Cheng, Genetic Algorithms and Engineering Design, John Wiley and Sons, New York, 1997.
18. Taguchi, G., S. Chowdhury and S. Taguchi, Robust Engineering, McGraw-Hill, New York, 2000.
19. Wu, Y., Taguchi Methods for Robust Design, The American Society of Mechanical Engineers, New York, 2000.
20. Rao, S. S., Mechanical Vibrations, Addison-Wesley, New York, 1995.