Design of RCGA-based PID controller for two-input two-output system Lee, Yun-Hyung; Kwon, Seok-Kyung; So, Myung-Ok;
Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.
A. Niederlinski, "A heuristic approach to the design of linear multivariable interating control system," Automatica, vol. 7, no. 6, pp. 691-701, 1971.
S. Skogestad and M. Morari, "Robust performance of decentralized control systems by independent designs," Automatica, vol. 25, no.1, pp. 119-125, 1989.
M. Chiuand and Y. Arkun, "A methodology for sequential design of robust decentralized control systems," Automatica, vol. 28, no. 5, pp. 997-1001, 1992.
M. Hovd and S. Skogestad, "Sequential design of decentralized controllers," Automatica, vol. 30, no. 10, pp. 1601-1607, 1994.
E. Gagnon, A. Pomerleau, and A. Desbiens, "Mu-synthesis of robust decentralized PI controllers," IEE. Proceedings of Control Theory Application, vol. 146, no. 4, pp. 289-294, 1999.
T. H. Um and B. S. Suh, "A LQ-PI controller tuning for TITO system," The Institute of Electronics Engineers of Korea, vol. 41, no. 5, pp. 275-280, 2004.
G. G. Jin, Genetic Algorithms and Their Application, Kyowoosa, 2004.
D. E. Kim and G. G. Jin, "Model-based tuning rules of the PID controller using real-coded genetic algorithms," Journal of Institute of Control, Robotics and Systems, vol. 8, no. 12, pp. 1056-1060, 2002.