Name
Abstract | ||
|---|---|---|
This article considers a finite-time stabilization problem of nonlinear systems with actuator failures. The controlled system is in non-strict-feedback form and the system states are immeasurable. By utilizing a structure property of neural network in Lemma 4, the design difficulty caused by non-strict-feedback form is handled. By establishing a state observer and applying the approximation property of neural network, a new adaptive output-feedback control scheme is formed. Under the proposed strategy, the actuator fault is compensated successfully. Different from the existing fault-tolerant control studies, the presented adaptive output-feedback control scheme can guarantee the stability of nonlinear systems in finite time, which is of more theoretical and practical significance. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ins.2019.05.067 | Information Sciences |
Keywords | Field | DocType |
Adaptive control,Finite-time control,Unknown actuation failures,Non-strict-feedback form | State observer,Nonlinear system,Control theory,Artificial intelligence,Finite time control,Observer (quantum physics),Artificial neural network,Approximation property,Machine learning,Mathematics,Lemma (mathematics),Actuator | Journal |
Volume | ISSN | Citations |
500 | 0020-0255 | 5 |
PageRank | References | Authors |
0.38 | 0 | 5 |