Low order robust controller design for preserving H∞ performance: Genetic algorithm approach

ISA Transactions

Volumn 43, Issue 4, 2004, Pages 539-547

  Lee, Ching Hung ^a  

^a YUAN ZE UNIVERSITY   (Taiwan)

Author keywords

Genetic algorithms; H ; Low order controller

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER SIMULATION; CONTROL SYSTEMS; GENETIC ALGORITHMS; LINEAR SYSTEMS; MATHEMATICAL MODELS; OPTIMAL CONTROL SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION; PROBLEM SOLVING;

FEEDBACK LOOP; LOW ORDER CONTROLLERS; PARAMETER SPACE; ROBUST CONTROLLER DESIGN;

ROBUSTNESS (CONTROL SYSTEMS);

EID: 7544244532     PISSN: 00190578     EISSN: None     Source Type: Journal    
DOI: 10.1016/s0019-0578(07)60167-0     Document Type: Article

References (31)

1. Doyle, J. C., Francis, B., and Tannenbaum, A., Feedback Control Theory. Maxwell/Macmillan, New York, 1992.
2. Doyle, J. C., Zhou, K., and Glover, K., Robust and Optimal Control. Prentice Hall, Upper Saddle River, NJ 1996.
3. Francis, B. and Doyle, J. C., Linear control with an H∞ optimality criterion. SIAM J. Control Optim. 25, 815-844 (1987).
4. Boyd, S. and Barrat, C. H., Linear Controller Design Limits of Performance. Prentice-Hall, Englewood Cliffs, NJ, 1991.
5. Bhattachayya, S. P., Chapellat, H., and Keel, L. H., Robust Control: The Parametric Approach. Prentice Hall, Englewood Cliffs, NJ, 1995.
6. Weinmann, A., Uncertain Models and Robust Control. Springer-Verlag, Berlin, 1992.
7. Glover, K. and Doyle, J. C., A state space approach to H∞ optimal control, in Three Decades of Mathematical Systems Theory. A Collection of Surveys at the Occasion of the 50th Birthday of Jan C. Willems, edited by H. Nijmeijer and J. M. Schumacher, Lecture Notes in Control and Information Sciences No. 135. Springer-Verlag, Berlin, 1989.
8. Astrom, K. J. and Hagglund, T., The future of PID Control. Control Eng. Pract. 9, 1163-1175 (2001).
9. Tang, K. K., Wang, Q. G., and Hang, C. C., Advances in PID Control. Springer, New York, 1999.
10. Siljak, D., Analysis and synthesis of feedback control systems in the parameters plane. IEEE Trans. Appl. Ind. 83, 449-473 (1964).
11. Boyd, S., Ghaoui, L. El., Feron, E., and Balakrishnan, Linear Matrix Inequalities in System and Control Theory. SIAM, Philadephia, 1994.
12. Goddard, P. J. and Glover, K., Controller approximation: Approaches for preserving H∞ performance. IEEE Trans. Autom. Control 43, 858-871 (1998).
13. Datta, A., Ho, M. T., and Bhattacharyya, S. P., Structure and Synthesis of PID Controllers. Springer, New York, 2000.
14. Chen, B. M., H∞ Control and Its Applications. Springer, New York, 1998.
15. Smith, M. C., On minimal-order controllers of single loop plants. Syst. Control Lett. 7, 39-40 (1986).
16. Gu, D. W., Choi, W., and Postlethwaite, I., Low-order stabilizing controller. IEEE Trans. Autom. Control 38, 1713-1717(1993).
17. Wang, Q. G., Lee, T. H., and He, J. B., Low-order stabilizers for linear systems. Automatica 33, 651-654 (1997).
18. Wang, Q. G., Lee, T. H., and He, J. B., Towards minimal-order stabilizer for all-pole plants. Syst. Control Lett. 31, 49-57 (1997).
19. Zhang, W. D. and Xu, X. M., On minimal-order stabilization of minimum phase plants. Automatica 38, 1243-1246 (2002).
20. Davis, L., Handbook of Genetic Algorithms. International Thomson Computer Press, New York, 1991.
21. Goldberg, D. E., Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley, Reading, MA, 1989.
22. Lin, C. T. and Lee, C. S. G., Neural Fuzzy Systems. Prentice Hall, Englewood Cliffs, NJ, 1996.
23. Man, K. F., Tang, K. S., and Kwong, S., Genetic algorithms: Concepts and applications. IEEE Trans. nd. Electron. 43, 519-534 (1996).
24. Michalewicz, Z., Genetic Algorithms+Data Structure = Evolutionary Programs, 3rd ed. Springer-Verlag, Berlin, 1997.
25. MATLAB 6.0: User's guide The Math Works, Inc., 1997.
26. Huang, Y. P. and Huang, C. H., Real-valued genetic algorithm for fuzzy grey prediction system. Fuzzy Sets Syst. 87, 265-276 (1997).
27. Tsutsui, S. and Goldberg, D. E., Search space boundary extension method in real-coded Genetic algorithm. Inf. Sci. (N.Y.) 133, 229-247 (2001).
28. Blanco, A., Delgado, M., and Pegalajar, M. C., A realcoded genetic algorithm for training recurrent neural networks. Neural Networks 14, 93-105 (2001).
29. Lee, C. H. and Teng, C. C., Tuning of PID Controller for stable and unstable processes with specifications on gain and phase margins. Int. J. Fuzzy Syst. 3, 346-355 (2001).
30. Hsia, T. C., System Identification: Least-Squares Methods. Heath, New York, 1977.
31. Kuo, B. C., Automatic Control Systems. 6th ed. Prentice-Hall, Englewood Cliffs, NJ, 1995.