Please use this identifier to cite or link to this item: http://rportal.lib.ntnu.edu.tw:80/handle/77345300/31995
Title: Compact Ant Colony Optimization Algorithm Based Fuzzy Neural Network Backstepping Controller for MIMO Nonlinear Systems
Authors: 國立臺灣師範大學電機工程學系
W.-Y. Wang
C.-K. Chen
Y.-G. Leu
C.-Y. Chen
Issue Date: 3-Jul-2010
Abstract: In this paper, a compact ant colony algorithm used to tune parameters of fuzzy-neural networks is proposed for function approximation and adaptive control of nonlinear systems. In adaptive control procedure for nonlinear systems, weights of the fuzzy neural controller are online adjusted by the compact ant algorithm in order to generate appropriate control input. For the purpose of evaluating the stability of the closed-loop systems, an energy fitness function is used in the ant algorithm. Finally, a computer simulation example demonstrates the feasibility and effectiveness of the proposed method.
URI: http://rportal.lib.ntnu.edu.tw/handle/77345300/31995
Other Identifiers: ntnulib_tp_E0604_02_018
Appears in Collections:教師著作

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.