Adaptive actuator fault tolerant control for uncertain nonlinear systems with multiple actuators. (English) Zbl 1331.93117
Summary: In this paper, a novel adaptive fault tolerant controller design is proposed for a class of nonlinear unknown systems with multiple actuators. The controller consists of an adaptive learning-based control law, a Nussbaum gain, and a switching function scheme. The adaptive control law is implemented by a two-layer neural network to accommodate the unknown system dynamics. Without the requirement of additional fault detection mechanism, the switching function is designed to automatically locate and turn off the unknown faulty actuators by observing a control performance index. The asymptotic stability of the system output in the presence of actuator failures is rigidly proved through standard Lyapunov approach, while the other signals of the closed-loop system are guaranteed to be bounded. The theoretical result is substantiated by simulation on a two-tank system.
MSC:
| 93C40 | Adaptive control/observation systems |
| 93B35 | Sensitivity (robustness) |
| 93C41 | Control/observation systems with incomplete information |
| 93C10 | Nonlinear systems in control theory |
| 92B20 | Neural networks for/in biological studies, artificial life and related topics |
| 93D20 | Asymptotic stability in control theory |
Keywords:
actuator fault tolerant control; neural networks; Nussbaum gain; uncertain nonlinear systemsReferences:
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