Design and Experimental Evaluation of Self-tuning Intelligent PID Controller using Genetic Algorithm

Y. Mitsukura, M. Fukumi, and T. Yamamoto (Japan)


PID control, generalized minimum variance control (GMVC) law, genetic algorithm


PID control schemes have been widely used in most of process control systems for the control of chemical processes. However the selection of suitable or optimal tuning parameters for such control laws remains a challenging problem. The PID constants have a great influence on stability and control performance. In this paper, a self-tuning PID control scheme is proposed, which is able to deal with a time varying system. The proposed scheme is derived based on the relationship between PID control and generalized minimum variance control(GMVC) laws. Furthermore, a suitable set of some user-specified parameters included in the GMVC criterion is sought by using a genetic algorithm re cursively. Finally, the newly proposed scheme is evaluated on a temperature control system.

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