Cover
Vol. 7 No. 1 (2011)

Published: May 31, 2011

Pages: 25-34

Original Article

Designing robust Mixed H /H PID Controllers based Intelligent Genetic Algorithm

Abstract

It's not easy to implement the mixed / optimal controller for high order system, since in the conventional mixed / optimal feedback the order of the controller is much than that of the plant. This difficulty had been solved by using the structured specified PID controller. The merit of PID controllers comes from its simple structure, and can meets the industry processes. Also it have some kind of robustness. Even that it's hard to PID to cope the complex control problems such as the uncertainty and the disturbance effects. The present ideas suggests combining some of model control theories with the PID controller to achieve the complicated control problems. One of these ideas is presented in this paper by tuning the PID parameters to achieve the mixed / optimal performance by using Intelligent Genetic Algorithm (IGA). A simple modification is added to IGA in this paper to speed up the optimization search process. Two MIMO example are used during investigation in this paper. Each one of them has different control problem.

References

  1. M. Hung, L. Shu, S. Ho, S. Hwang, and S. Ho, "A Novel Intelligent Multiobjective Simulated Annealing Algorithm for Designing Robust PID Controllers", IEEE Trans. on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 38, no. 2, March 2008.
  2. B. Chen and Y. Cheng, "A Structure-Specified H Optimal Control Design for Practical Applications: A Genetic Approach", IEEE Trans. on Control Systems Technology, vol. 6, November 1998.
  3. M. Zeren and H. Özbay, "On the Synthesis of Stable H Controllers", IEEE Trans. on Automatic Control, vol. 44, no. 2, February 1999.
  4. B. Chen, Y. Cheng, and C. Lee, "A Genetic Approach to Mixed H/H Optimal PID Control", IEEE, October 1995.
  5. S. Scogestad and I. Postlethwaite, *Multivariable Feedback Control*, New York: Wiley, 1996.
  6. H. A. Hindi, B. Hassibi, and S. P. Boyd, "Multiobjective H/H Optimal Control via Finite Dimensional Q-Parameterization and Linear Matrix Inequalities."
  7. L. Mianzo and H. Peng, "Output Feedback H Preview Control of an Electromechanical Valve Actuator", IEEE Trans. on Control Systems Technology, vol. 15, no. 3, May 2007.
  8. R. Haupt and S. Haupt, *Practical Genetic Algorithm*, 2nd edition, 2004.
  9. S. Ho, L. Shu, and J. Chen, "Intelligent Evolutionary Algorithms for Large Parameter Optimization Problems", IEEE Trans. on Evolutionary Computation, vol. 8, no. 6, December 2004.
  10. S. Ho, S. Ho, and L. Shu, "OSA: Orthogonal Simulated Annealing Algorithm and Its Application to Designing Mixed H/H Optimal Controllers", IEEE Trans. on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 34, no. 5, September 2004.
  11. I. Kitsios, T. Pimennides, and P. Groumpos, "A Genetic Algorithm for Designing H Structured Specified Controllers", IEEE Int. Conf. on Control Applications, September 5-7, 2001.
  12. S. Ho, S. Ho, M. Hung, L. Shu, and H. Huang, "Designing Structure-Specified Mixed H/H Optimal Controllers Using an Intelligent Genetic Algorithm (IGA)", IEEE Trans. Control Systems Technology, vol. 13, no. 6, November 2005.
  13. W. Tan, T. Chen, and H. J. Marquez, "Robust Controller Design and PID Tuning for Multivariable Processes", Asian Journal of Control, vol. 4, no. 4, pp. 439-451, December 2002.
  14. Q. G. Wang, Q. Zou, T. H. Lee, and Q. Bi, "Auto-tuning of Multivariable PID Controllers From Decentralized Relay Feedback", Automatica, vol. 33, 1997.
  15. J. W. Dong and G. B. Brosilow, "Design of Robust Multivariable PID Controllers via IMC", Proc. American Control Conference, Albuquerque, New Mexico, 1997.