Investigations on Metaheuristic Algorithm for Designing Adaptive PID Controller for Continuous Stirred Tank Reactor

Abstract

An integral part of industrial processes is the Continuous Stirred Tank Reactor (CSTR) whose dynamic characteristics are highly nonlinear causing the reactor to deviate from its set temperature point. For its efficient operation, specific parameters of the CSTR are required to be controlled. Hence, this paper presents designing of the Proportional-Integral-Derivative (PID) controller using conventional and metaheuristic methods for the temperature control of the CSTR. The conventional controller is tuned with Ziegler Nichols (Z-N) method. Global search population-based metaheuristic methods like Artificial Bee Colony (ABC), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) have been implemented to optimize the adaptive controller parameters, and a comparative analysis is done taking the step response into consideration. The CSTR system is simulated by the proposed controller which improves the robustness, behaviour and tracking of the system. The simulation results present substantial enhancement of the time response parameters, i.e. settling time, rise time, peak overshoot, mean square error and integral time absolute error. Studies showed that the proposed adaptive methods with metaheuristic algorithms are fast and efficient in error reduction. Here, ABC irrespective of other optimization methods suitably optimized the controller parameters.