Adaptive Event-triggered Control for Networked Switched T-S Fuzzy Systems Subject to False Data Injection Attacks
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ISSN:1598-6446 eISSN:2005-4092 http://www.springer.com/12555
Adaptive Event-triggered Control for Networked Switched T-S Fuzzy Systems Subject to False Data Injection Attacks Yiwen Qi*, Shuo Yuan, and Xin Wang Abstract: This paper is concerned with the problem of adaptive event-triggered control for networked switched T-S fuzzy systems under false data injection attacks. In order to reduce unnecessary data transmission, an adaptive event-triggering mechanism is proposed, which can dynamically change triggering conditions based on system performance needs. In particular, due to the consideration of network safety, the system will be subjected to the impacts from both attack delays and network transmission delays. Then, by a delay system transformation approach, a time-delay closed-loop switched T-S fuzzy system is obtained. Moreover, by utilizing average dwell time technique, stability conditions are developed for the closed-loop system with the adaptive event-triggering mechanism and false data injection attacks. In addition, a co-design of adaptive event-triggering parameters and controller gains is given. Finally, simulation results are provided to verify the effectiveness of the designed method. Keywords: Adaptive event-triggered control, average dwell time, false data injection attacks, switched T-S fuzzy systems.
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INTRODUCTION
With the rapid development of modern computers and network technique, networked control systems (NCSs) have come to the fore [1,2]. Due to remarkable advantages of NCSs in reducing maintenance costs and ease of installation and information sharing, it is widely applied in various practical areas [3,4]. However, the limited bandwidth of the network inevitably brings some inherent physical limitations, which could seriously damp the system performances. To reasonably allocate the system resources and improve network communication utilization, eventtriggered control is proposed in [5], which can implement data sampling depending on a certain event-triggering condition. Achievements of event-triggered control have been received and different event-triggering mechanisms are obtained. For example, a discrete event-triggering mechanism is presented to deal with the Zeno behaviors, and a time-delay system modeling method is utilized in [5]. In [6], a performance dependent event-triggering mechanism for networked switched systems with dynamic output feedback is considered. In [7], an adaptive event-
triggering mechanism is introduced, and an adaptive law is given to automatically change the corresponding threshold. A hybrid-triggering mechanism is presented for TS fuzzy systems subject to stochastic cyber attacks in [8]. Besides, there are some other typical mechanisms in the literature, e.g., decentralized event-triggering mechanism [9], stochastic event-triggering mechanism [10] and switched event-triggering mechanism [11]. On the other hand, switched systems have received extensive attention due to their application in practical multimode industrial systems [12–14]. Switched systems are
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