Dynamic event-triggered synchronisation control for complex dynamical networks with stochastic attacks and actuator faults

ABSTRACT

This paper studies the problem of dynamic adaptive event-triggered synchronisation control for a class of complex dynamical networks (CDNs) with parameter uncertainty and stochastic network attacks. In order to save communication resources, reduce the driving burden and overcome the conservatism of fixed parameters, an improved event-triggered control strategy is designed. Firstly, a new synchronisation error model with uncertain of internal coupling weights between nodes and stochastic network attacks on actuator is modelled. Secondly, the Bernoulli stochastic distribution process is used to describe the probability of stochastic attacks, and the actuator failure model is adopted to depict actuator failure. By establishing an appropriate Lyapunov function, some sufficient conditions to ensure the asymptotic stability of the synchronisation error system is derived, which reduces conservatism. In addition, the cooperative design of controller and adaptive event-triggered strategy is solved by solving linear matrix inequality. Eventually, two examples are given to illustrate the effectiveness and potential of the proposed design method.

KEYWORDS:

• Complex dynamical networks
• dynamic event-triggered synchronisation control
• stochastic attacks
• actuator faults
• adaptive control strategy

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author [Ma, Y.], upon reasonable request.

Additional information

Funding

This work is partially supported by the National Natural Science Foundation of China [grant number 61273004], and the Natural Science Foundation of Hebei Province [grant number F2021203061].

Notes on contributors

Guiying Zang

Guiying Zang was born in 1995. She received the B.S. degree from Yuncheng University, Yuncheng, China, in 2019. She is currently a Master degree candidate in the School of Science, Yanshan University, China .Her current research interests include complex networks, time-delay systems, event-triggered control, etc.

Shengli Shi

Shengli Shi was born in 1979. He received the B.S. degree in Mathematics from Shandong University in 2002, and the Ph.D. degree in control science and engineering from Yanshan University in 2014. He is currently an associate professor with the School of Science, Yanshan University. His research interests include robust control and disturbance compensation.

Yuechao Ma

Yuechao Ma was born in 1963. He received the B.S. degree from Northeast Normal University, Changchun, China, in 1984. He received his PhD degree from Northeast University, Shenyang, China, in 2006. He is currently a full professor in the School of Science, Yan shan University, China. His current research interests include linear and nonlinear control, neural networks, robust control and time-delay system theory.