A Novel PID Neural Network Controller based on Memristor

In this paper, an effective optimize method based on adaptive PID neural network controller is presented. Chaotic Particle Swarm Optimization (CPSO) is introduced to initialize the parameters of neural network for improving the convergent speed and preventing weights trapping into local optima. In order to realize the hardware platform of PID neural network controller and facilitate weight update algorithm, the nanoscale memristor is utilized to analog electronic synapse. Meanwhile, the stability of closed-loop system is further proved by Lyapunov theory. Based on several comparative experiments on automatic voltage regulation system, the final results illustrate that the proposed controller can obtain better precision in a shorter time.