Robust control for nonlinear systems by Universal Learning Network considering fuzzy criterion and second order derivatives

Masanao Ohbayashi, Kotaro Hirasawa, Katsuyuki Toshimitsu, Junichi Murata, Jinglu Hu

Research output: Contribution to conferencePaper

Abstract

Control systems using neural networks have been used recently 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 this paper, a new robust control method is proposed, which is based on the second order derivatives of Universal Learning Network and fuzzy criterion function.

Original languageEnglish
Pages968-973
Number of pages6
Publication statusPublished - 1998 Jan 1
EventProceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) - Anchorage, AK, USA
Duration: 1998 May 41998 May 9

Other

OtherProceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3)
CityAnchorage, AK, USA
Period98/5/498/5/9

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ASJC Scopus subject areas

  • Software

Cite this

Ohbayashi, M., Hirasawa, K., Toshimitsu, K., Murata, J., & Hu, J. (1998). Robust control for nonlinear systems by Universal Learning Network considering fuzzy criterion and second order derivatives. 968-973. Paper presented at Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3), Anchorage, AK, USA, .