Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4944234 | Information Sciences | 2017 | 12 Pages |
Abstract
This paper addresses the control problem of MIMO stochastic nonlinear systems with unknown high-frequency gains. In the existing works, the prior knowledge of the high-frequency gain or its control direction is assumed known for the control design. This paper removes such assumptions, and proposes an adaptive neural network algorithm that allows the high-frequency gains to be time-varying and their control directions to be unknown. Nussbaum gain based approach and adaptive neural network mechanism are brought together such that all the signals in the closed-loop system are ensured bounded. A simulation study is carried out to confirm the validity of the proposed algorithm.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Ci Chen, Zhi Liu, Kan Xie, Yun Zhang, C.L. Philip Chen,