| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 411085 | Neurocomputing | 2010 | 9 Pages |
Abstract
An adaptive control scheme combined with backstepping, radial basis function (RBF) neural networks is proposed for the output tracking control problem of a class of MIMO nonlinear systems with input delay and disturbances. Neural networks are employed to estimate the unknown continuous functions. The control scheme ensures that the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB). The tracking error is proved to be bounded and ultimately converges to an adequately small compact set. The feasibility is investigated by a simulation example.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Qing Zhu, Tianping Zhang, Shumin Fei,