Title :
Performance Enhancement of Multiple Model Adaptive Control by Using Neural Networks
Author :
Li, Xiaoli ; Zhang, Yan ; Qian, Xiaolong
Author_Institution :
Univ. of Sci. & Technol. Beijing, Beijing
Abstract :
Multiple linear and BP NN (back propagation neural network) models are used to approximate the complex nonlinear system, and different model reference adaptive controllers based on these models and different switching mechanisms are applied to a nonlinear system to trace a reference trajectory. From the simulation, it can be shown that the multiple model adaptive control method proposed in this paper can improve the control performance greatly compared with conventional adaptive neural network controller.
Keywords :
backpropagation; large-scale systems; model reference adaptive control systems; neurocontrollers; nonlinear control systems; adaptive neural network control; backpropagation neural network; complex nonlinear system; model reference adaptive control; multiple linear neural network; multiple model adaptive control; performance enhancement; reference trajectory; Adaptive control; Convergence; Design automation; Design engineering; Error correction; Multi-layer neural network; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; adaptive control; multiple model; neural network;
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
DOI :
10.1109/ICAL.2007.4338925
