Application of Particle Swarm Optimization Algorithm in Continuous Stirred Tank Reartnr (CSTR) Control System

Particle swarm optimization (PSO) algorithm is a commonly used optimization algorithm that analyzes and improves discretization problems by establishing models. This article will first introduce the PSO method and its basic principles. Then, this article proposes a new controller design idea based on the combination of PSO algorithm, robustness test and other related constraints to solve the above two control problems. Finally, this article applies the controller to a continuously stirred reactor to realize simulation and analysis of the model's operation process. The simulation results show that the deviation range of the system is 0.02-0.08; the absolute error range is 0.1-0.4; the percentage error range is 0.02-0.08; the stability range of the overshoot is 80%-87%; the stability range of the adjustment time is between 80% and 89%; the accuracy of the control output value and the expected output value are above 93% and above 90% respectively. To sum up, this controller has good global convergence performance and can effectively improve the control effect of the system.