By Topic

Robust control for nonlinear systems by universal learning network considering fuzzy criterion and second order derivatives

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Ohbayashi, M. ; Dept. of Electr. & Electron. Syst. Eng., Kyushu Univ., Fukuoka, Japan ; Hirasawa, K. ; Toshimitsu, K. ; Murata, J.
more authors

Control systems using neural networks have been used in many fields, but some problems remain unsolved. One of the problems which should be overcome is to enhance the robustness of the neural network control systems. In the paper, a robust control method is proposed, which is based on the second order derivatives of the universal learning network and fuzzy criterion function

Published in:

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on  (Volume:2 )

Date of Conference:

4-9 May 1998