An Artificial Intelligent Method for Tuning of PID Controller

This Paper tries to explore the potential of using artificial intelligence method in controllers and their advantages over conventional methods. PID controller, being the most widely used controller in industrial applications, needs efficient method to control the different parameters of the plant. This Paper asserts that the conventional approach of PID tuning is not very efficient due to the presence of non-linearity in the system of the plant. The output of the conventional PID system has a quite high overshoot and settling time. Tuning of the PID parameters continues to be important as these parameters have a great influence on the stability and performance of the control system. This paper proposes a method based on the ant colony optimization technique (ACO) to determine the parameters of the Proportional Integral Derivative (PID) controller for getting best performance for a given plant. The method searches the PID parameter that realizes the expected step response of the plant. It is based upon maximization of a fitness function. The plant model is represented by the transfer function T(s) of a low damping plant. The PID parameter is computed by ACO-based PID tuning method. The method show the effectiveness of the proposed tuning method.