Intelligent Internal Model Pid Control Method

This paper summarizes the present research situation on internal model PID control scheme (IMC-PID). New IMC-PID control algorithms based on fuzzy logic and neural network are proposed.Firstly, an IMC-PID control method with set-point weight is presented. The set-point weight of the proportional part of the IMC-PID controller is modified online by fuzzy logic, so the command tracking and the disturbance rejection can be greatly improved. Not only the method can improve the conventional IMC-PID controller, but also it is simple and the control parameters can be adjusted easily.Secondly, an IMC-PID controller based on neural network is proposed. The parameters of IMC-PID controller can be tuning online by the neural network, so the robustness and adaptive ability are greatly improved. The better control performance can be achieved for the process with time delay, even in the case that its parameters change.At last, an IMC-PID controller based on fuzzy gain scheduling method is proposed for unstable first-order plus delay (FODUP) system. Fuzzy controller is utilized on-line to regulate the controller parameters based on the error signal and its first derivative. The method adjusts the IMC-PID controller parameter trying to overcome the tradeoff between command tracking and disturbance rejection, and the control system performance is improved.Theoretical analysis and simulation results show the validity of these control schemes.