Adaptive Neural Control Approach for Switched Nonlinear Discrete-Time Systems With Actuator Faults and Input Dead Zone
In this paper, an adaptive control strategy is developed for discrete-time switched nonlinear systems with actuator faults and dead-zone input under arbitrary switching conditions. The actuator faults considered include loss-of-effectiveness and bias faults, which are unknown but bounded. The comple...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/ddns/2364395 |
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| Summary: | In this paper, an adaptive control strategy is developed for discrete-time switched nonlinear systems with actuator faults and dead-zone input under arbitrary switching conditions. The actuator faults considered include loss-of-effectiveness and bias faults, which are unknown but bounded. The complex structure of these systems, combined with actuator faults and dead-zone inputs, presents significant challenges for control and this problem is addressed by approximating the unknown functions of each subsystem using radial basis function neural networks. Under arbitrary switching signals, the suggested controller and adaptive laws ensure that all signals remain bounded and the system output tracks the reference signal with a small bounded tracking error. The efficiency of the control technique is proven by two numerical examples. |
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| ISSN: | 1607-887X |