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
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;
Conference_Titel :
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location :
Hefei
Print_ISBN :
0-7803-5995-X
DOI :
10.1109/WCICA.2000.863412
