抄録
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.
| 本文言語 | English |
|---|---|
| ページ | 2453-2458 |
| ページ数 | 6 |
| 出版ステータス | Published - 1998 1 1 |
| 外部発表 | はい |
| 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
| 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
- ソフトウェア