Title :
RBF Neural Network and Its Application in IMC
Author :
Qu, Yang ; Xu, Lin ; Wang, Jianhui ; Fang, Xiaoke ; Gu, Shusheng
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang
Abstract :
The IMC controller based on RBF adaptive neural network is designed by the capacity of nonlinear approach of RBF neural network. The problem of nonlinear and uncertainty bound is solute. The weigh coefficient that is difference between expectation output of internal model and output of the object is designed. The recurrence learn algorithm is used to carry out RBF neural network cluster center by SOFM neural network, and recurrence least square is used to fix on weigh of RBF neural network The simulation results show that new method leads to improve dynamic performance and robustness
Keywords :
neurocontrollers; nonlinear control systems; radial basis function networks; robust control; self-organising feature maps; IMC controller; RBF neural network; SOFM neural network; internal model control; recurrence learn algorithm; robustness; Adaptive systems; Design engineering; Educational institutions; Electronic mail; Information science; Intelligent networks; Neural networks; Programmable control; Recurrent neural networks; Three-term control; IMC; RBF neural network; inverse model; nonlinear system; speed control;
Conference_Titel :
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location :
Dalian
Print_ISBN :
1-4244-0332-4
DOI :
10.1109/WCICA.2006.1712792
