Soft computing techniques based optimal tuning of virtual feedback PID controller for chemical tank reactor

CSTR plays a vital role in almost all the chemical reactions and is a highly nonlinear system exhibiting stable as well as unstable steady states. The variables which characterize the quality of the final product in CSTR are often difficult to measure in real-time and cannot be directly measured using the feedback configuration [1]. So, a virtual feedback control is implemented to control the state variables using Extended Kalman Filter (EKF) in the feedback path. Since it is hard to determine the optimal or near optimal PID parameters using classical tuning techniques like Ziegler Nichols method, a highly skilled optimization algorithm like Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) are used. This work is based on the optimal tuning of virtual feedback PID control for a CSTR system using soft computing algorithm for minimum Integral Square Error (ISE) condition.