Adaptive control of nonlinear black-box systems based on Universal Learning Networks

Jinglu Hu, Kotaro Hirasawa, Junichi Murata, Masanao Ohbayashi, Kousuke Kumamaru

Research output: Contribution to conferencePaper

Abstract

This paper presents an adaptive control scheme for nonlinear black-box systems based on the use of Universal Learning Networks (ULN). A ULN nonlinear controller is constructed in a similar way to linear stochastic control theory. In the obtained ULN controller, some node functions are known, while others are unknown. Each unknown node function is re-parameterized using an adaptive fuzzy model. A robust adaptive algorithm is developed to adjust the unknown parameters in the controller. The effectiveness of the proposed control scheme is examined via numerical simulations.

Original languageEnglish
Pages2453-2458
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

ASJC Scopus subject areas

  • Software

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    Hu, J., Hirasawa, K., Murata, J., Ohbayashi, M., & Kumamaru, K. (1998). Adaptive control of nonlinear black-box systems based on Universal Learning Networks. 2453-2458. Paper presented at Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3), Anchorage, AK, USA, .