Evolutional Based Optimization Analysis for Three-element Control System

This paper presents a multi-objective optimization analysis to improve the controller tuning of three-element control loop for the best fit to both its servo and regulatory control objectives during the process operations. The existing Proportional-Integral-Derivative (PID) controller tuning for the three-element control loop is challenging because the best setting of each controller is obtained during the concurrent analysis, but all controller settings affect the control performance of other control loops and the output responses. Furthermore, this paper highlights the determination of Upper Limit (UL) and Lower Limit (LL) bounds by using the necessity criterion of Routh-Hurwitz stability analysis. The Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used as the optimization algorithms to improve the control performances. Both optimization analysis are operated by using a developed Graphical User Interface (GUI) via MATLAB software. At the same time, the optimized PID controller settings are applied to the steam boiler drum function of the LOOP-PRO simulator. Both GA and PSO outperform the manual tuning for the three-element loop. Among them, GA performs better than PSO even though both methods are capable of suggesting highly satisfactory performances.