Optimal Tuning of PID Controller for a Continuous Stirred Tank Reactor (CSTR) Using Ant Colony Optimization

Abstract

Ant colony optimization (ACO)-based proportional integral derivative (PID) controller has been proposed for tuning optimized PID parameters in a continuous-stirred tank reactor (CSTR) process. In our proposed work, we have found that the tuning should have minimum value for rise time, peak time, settling time, etc. to be effective to design a CSTR system by optimal PID tuning. The simulation results of the proposed work reveal that the ACO-based PID tuning gives satisfactory performance in terms of minimum value of rise time, peak time, settling time, etc., and is the effective AI technique to design a CSTR system.

Keywords: ant colony optimization (ACO), CSTR, optimal tuning. PID controller