A CMAC Based Self-Tuning Intelligent PID Controller for Electric Load Simulator

摘要

With the advantages of quick learning, simple structure, nonexistent local optimum and good real-time performance, the Cerebella Model Articulation Controller (CMAC) has been widely used in the control of nonlinear systems. In this paper, the genetic algorithm is used to identify uncertain parameters of electric load simulator to improve the credibility of the mathematical model. Then a CMAC-based self-tuning intelligent PID controller is proposed for electric load simulators. The simulation and experimental results demonstrate that the proposed intelligent PID controller has good robustness and can effectively eliminate the surplus torque with high control precision.