Soft Computing Techniques Based Design of Feedback PID Controller for an Industrial Process

Proportional Integral derivative (PID) controllers are widely used in industrial process control. With its three term functionality providing regulation to both transient and steady state responses, PID control offers the simplest and most efficient solution to many industrial control problems. Tuning of PID gain parameters continuous to be important as these parameters has great influence on the stability and the performance of the control system. Many techniques are used to tune PID controller. In this paper, Soft Computing technique Genetic Algorithms are proposed as a method for tuning of PID controller. The performance of Genetic Algorithms based PID controller is compared with feedback PID controller tuned by trial and error method, feedback plus feedforward controller, Zeigler-Nicholas PID controller. Shell and tube heat exchanger process is used for performance analysis of different controllers. Simulation results show that the gains obtained using Genetic Algorithms provide better performance than those obtained by Ziegler-Nicholas method and other controllers.