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.
|出版ステータス||Published - 1998 1 1|
|イベント||Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) - Anchorage, AK, USA|
継続期間: 1998 5 4 → 1998 5 9
|Other||Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3)|
|City||Anchorage, AK, USA|
|Period||98/5/4 → 98/5/9|
ASJC Scopus subject areas