DocumentCode
354223
Title
Nonlinear model predictive control based on multiple neural networks
Author
Zhihua, Xiong ; Xiong, Wang ; Yongmao, Xu
Author_Institution
Dept. of Autom., Tsinghua Univ., Beijing, China
Volume
2
fYear
2000
fDate
2000
Firstpage
1110
Abstract
Improved predictions can be obtained by using multiple neural networks instead of trying to find a single optimal network as usual. All the component networks of MNN model are selected using generalized information entropy, and the accuracy and reliability of overall model are significantly improved. Based on such an MNN model, a new nonlinear model predictive control algorithm is proposed. Simulation results of a pH CSTR demonstrates that the method is effective and practical
Keywords
entropy; neurocontrollers; nonlinear control systems; pH control; predictive control; process control; CSTR; entropy; model predictive control; multiple neural networks; nonlinear control control; pH control; process control; Automation; Continuous-stirred tank reactor; Information entropy; Multi-layer neural network; Neural networks; Prediction algorithms; Predictive control; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location
Hefei
Print_ISBN
0-7803-5995-X
Type
conf
DOI
10.1109/WCICA.2000.863412
Filename
863412
Link To Document