Adaptive event-triggered control for neural network-approximated switched systems under injection attacks
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL(2024)
Abstract
This paper studies the event-triggered control for uncertain switched systems under injection attacks. An adaptive event-triggered control method for neural network-approximated switched systems (NNA-SSs) is proposed. The main works are as follows: First, a neural network is introduced to approximate the uncertain nonlinear item of the systems. Second, the observer-based adaptive event-triggering (OB-AET) strategy is designed to efficiently utilize communication and computing resources. Furthermore, the closed-loop switched systems considering injection attacks are established. By utilizing the Lyapunov function method and average dwell time technique, sufficient conditions for the exponential stability of the closed-loop switched systems are given. Accordingly, the gains of the state feedback controllers and observers are solved. Finally, simulation examples are given to verify the effectiveness of the proposed method.
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Key words
Switched systems,observer-based adaptive event-triggering,uncertainty approximated by neural networks,false data injection attacks,multiple Lyapunov functions,average dwell time technique
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