Optimum Setting of Controller Using Soft Computing Techniques for a Chemical System

Abstract

Problem statement: The aim of this study is to present an intelligent tuning technique for PID controller that are simple and still result in good closed loop behavior. The idea is to start with a tuned conventional PID controller, replace it with an equivalent intelligent controllers like Fuzzy, ANN, Genetic and PSO techniques implies fine tuned nonlinear PID controller which is most suitable for nonlinear process like Continuous stirred tank reactor. The performance of various optimization techniques and intelligent techniques are compared. Approach: In this study we present soft computing techniques to design and tune the PID controller. The objective is tominimise the steady state error and to obtain the optimum response. Results: The comparisons amoung the Conventional PID, Fuzzy Sliding PID, Simulated Anneling PID and PSO tuned PID controllers PSO PID implies better result for the nonlinear chemical process. Conclusion: With the nonlinear model of CSTR process the PSO tuned PID controller implies the optimum response for both setpoint and load variations.