MODELLING AND SIMULATION OF NEURAL NETWORK BASED INTELLIGENT PID CONTROLLER FOR PRESSURE CONTROL USING BACK PROPAGATION ALGORITHM

Abstract

This paper gives a Neural Network PID controller based on Back Propagation (BP) algorithm connected to pressure control in a tank. The controller has numerous favorable circumstances like that more convenient in parameter managing, better hearty. Neural network is to modify the parameters of PID controller based on the operational status of the framework, to accomplish a superior execution, making the yield of the yield neurons corresponding to the three customizable parameters of a PID controller. Through neural network self-learning and weighting coefficient alteration, the neural network yield will corresponds to the PID controller parameters under a specific ideal control law. The simulation after effects of pressure control in a tank by utilizing Neuro-PID controller demonstrate that it can gain better power.