Genetic Algorithm Optimization Analysis for Temperature Control System using Cascade Control Loop Model

Abstract

This research presented a holistic approach in determining the trade-off optimized Proportional-Integral-Derivative (PID) tunings for both servo and regulatory controls of the cascade control loop by using Genetic Algorithm (GA). Performance of GA-based PID tunings was significantly compared with the IMC-based single loop tunings and conventional cascade control tunings. GA-based PID tunings eliminated the complicated mathematic calculations in obtaining the correlation PID tuning values and also reduce the dependency on engineering knowledge, experience, and skills. The performance of transient and steady-state responses was compared through time domain specification, performance index, and process response curve. It is concluded that the GA-based PID tunings for the cascade control loop had produced the best result for both servo and regulatory control objectives, which is eventually determined.