Optimal Tuning of PID Controller for a Continuous-Stirred Tank Reactor (CSTR) Using Particle Swarm Optimization

Abstract

Particle swarm optimization (PSO)-based proportional integral derivative (PID) controller has been proposed for tuning optimized PID parameters in a continuous-stirred tank reactor (CSTR) process. One of the main objectives in biochemical and chemical industries is optimization of PID controller parameters. The operating ranges of processes, with dynamic nonlinearity, have been specified by PID controllers. In our proposed work, we have found that the tuning, which has minimum value for rise time, peak time, settling time, etc., is the best AI technique to design a CSTR system by optimal PID tuning. The study of simulation reveals that the PSO-based PID controller provides satisfactory performance.

Keywords: CSTR, optimal tuning, particle swarm optimization (PSO), PID controller.