Design of PID Controller Based on RBF Neural Network

Since it can’t acquire satisfied control result by using traditional PID control for non-linear systems in industry control field.Radial basis function neural network is optimized based on gradient descent algorithm,and its model is constructed,then the M language program is written.By adjusting parameters of PID controller,the output approximately tracks the input.The method needs only initial parameters of PID controller,and the system performance relies on optimization adjustment of neural network.Thus,it can effectively solve parameter adjustment difficulties in classic PID control method,and can overcome adverse effects created by inaccurate parameter adjustment of PID control.