Memory-event-trigger-based secure control of cloud-aided active suspension systems against deception attacks

This paper investigates the problem of memory-based event-triggered fuzzy control for cloud-aided active suspension systems (ASSs) against deception attacks. A novel memory-based event-triggered mechanism (ETM) which is sensitive to deception attacks is proposed. Compared to the general ETM, the system under the memory-based ETM has a higher average data releasing rate during deception attacks and external disturbance. Therefore, a better suspension performance of the cloud-aided ASS can be obtained. Meanwhile, the system without deception attacks can maintain a lower average data releasing rate, thereby reducing the occupation of the network resource. Moreover, such a memory-based ETM can mitigate the occurrence of wrong triggering event that is generated by some abrupt variation of the input of ETM. Sufficient conditions that guarantee the desired performance of cloud-aided ASSs are derived. Finally, an example of quarter-vehicle suspension system is provided to verify the effectiveness of the proposed method.