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

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

Section of Measurement and Control Engineering

Research output: Contribution to conference › Paper › peer-review

9 Citations (Scopus)

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 language	English
Pages	968-973
Number of pages	6
Publication status	Published - 1998
Event	Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) - Anchorage, AK, USA Duration: May 4 1998 → May 9 1998

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Other	Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3)
City	Anchorage, AK, USA
Period	5/4/98 → 5/9/98

All Science Journal Classification (ASJC) codes

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Robust control for nonlinear systems by Universal Learning Network considering fuzzy criterion and second order derivatives. / Ohbayashi, Masanao; Hirasawa, Kotaro; Toshimitsu, Katsuyuki et al.
1998. 968-973 Paper presented at Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3), Anchorage, AK, USA.

Research output: Contribution to conference › Paper › peer-review

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

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.",

author = "Masanao Ohbayashi and Kotaro Hirasawa and Katsuyuki Toshimitsu and Junichi Murata and Jinglu Hu",

year = "1998",

language = "English",

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note = "Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) ; Conference date: 04-05-1998 Through 09-05-1998",

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AU - Ohbayashi, Masanao

AU - Hirasawa, Kotaro

AU - Toshimitsu, Katsuyuki

AU - Murata, Junichi

AU - Hu, Jinglu

PY - 1998

Y1 - 1998

N2 - 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.

AB - 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.

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M3 - Paper

AN - SCOPUS:0031644261

SP - 968

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T2 - Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3)

Y2 - 4 May 1998 through 9 May 1998

ER -

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

Abstract

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All Science Journal Classification (ASJC) codes

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