Self-tuning PID control of jacketed batch polystyrene reactor using genetic algorithm

Abstract

Self-tuning PID controller with genetic algorithm (GA) was applied to the temperature control of a jacketed batch polymerization reactor and thus tracking performance of optimal temperature profile was investigated. To obtain optimal tuning parameters of this controller, genetic algorithm was used. The fitness function for GA was taken as the integral of the absolute value of the error (IAE). By using tuning parameters three different optimal temperature trajectories were obtained, the efficiency and the performance of the self-tuning PID controller with GA was examined by simulation and experimentally. It was observed that the control experiments were successfully conducted on tracking the optimal trajectories which would yield polymer product with desired properties. Simulation results also show that self-tuning PID control with GA give very satisfactory results.