A new designing method of a robust neural network controller against system environment changes using Universal Learning Network (ULN) is considered in this paper. With the introduced method, the worst values of system parameters can be searched as well as the optimization of controller parameters through a dual learning algorithm, which includes maximization and minimization procedures. Therefore, the robust controller can be obtained by minimizing the criterion function regarding the worst values of system parameters. Simulation results demonstrate that the system performance has been improved compared with the conventional method by using the proposed method.
|出版ステータス||Published - 2001 1 1|
|イベント||International Joint Conference on Neural Networks (IJCNN'01) - Washington, DC, United States|
継続期間: 2001 7 15 → 2001 7 19
|Conference||International Joint Conference on Neural Networks (IJCNN'01)|
|Period||01/7/15 → 01/7/19|
ASJC Scopus subject areas
- Artificial Intelligence