Artificial Neural Network based PID controller for online control of dynamical systems

Abstract

For online control of various dynamical systems, an adaptive artificial neural network (ANN) based proportional integral derivative (PID) controller is developed. For linear time invariant processes, conventional PID controller is suitable but they have limitations when they are required to control the plants having high non linearity or their parameters are changing with the time. In order to find the parameters of PID controller, information regarding the dynamics of the plant is essential. If perturbation occurs in plant parameter(s) then PID controller may work only if these changes are not severe. But most plants are either non linear or their parameters changes with time and this demands for a use of more robust type of controller and ANN is a suitable candidate. To use the power of PID controller and ANN, ANN based PID controller is proposed in this paper. The benefit of this combination is that it utilizes the simplicity of PID controller mathematical formula and uses the ANN powerful capability to handle parameter variations and non linearity.