Model-Free Adaptive Control Based on Neural Network Observer for the Chaotic Power Supply System
Ao Bai, Yanhong Luo, Huaguang Zhang · 2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS) · 2020
In this paper, we considered a type of chaotic power supply system and presented a neural network adaptive method with Neural Network Observer (NNO). First, the mathematical model of the chaotic power supply system is summarized. Then aiming for the unknown model of n-order nonlinear system, the controller is designed by the neural network adaptive method. There is no need to know the accurate mathematical model and state information of the controlled object. We estimate the state information and model information of the controlled object through the input and output data of the object first, and use the obtained estimation results to implement the controller, and give the corresponding theoretical analysis. Finally, the effectiveness of the designed controller is verified by simulation of a power system with chaotic motion.