Mean Square Consensus of Nonlinear Multi-Agent Systems under Markovian Impulsive Attacks

Huan Luo,Yinhe Wang,Xuexi Zhang,Peitao Gao,Haoxiang Wen

doi:10.3390/app11093926

Abstract

This paper focuses primarily on the mean square consensus problem of a class of nonlinear multi-agent systems suffering from stochastic impulsive deception attacks. The attacks here are modeled by completely stochastic destabilizing impulses, where their gains and instants satisfy all distributions and the Markovian process. Compared with existing methods, which assume that only gains are stochastic, it is difficult to deal with systems with different types of random variables. Thus, estimating the influence of these different types on the consensus problem is a key point of this paper. Based on the properties of stochastic processes, some sufficient conditions to solve the consensus problem are derived and some special cases are considered. Finally, a numerical example is given to illustrate the main results. Our results show that the consensus can be obtained if impulsive attacks do not occur too frequently, and it can promote system stability if the gains are below the defined threshold.

Highlights

Consensus of Nonlinear Multi-AgentWith the development of hardware equipment and communication technology, the collaborative control problem has recently become the focus of studies of complex systems [1,2,3]
Under Assumptions 1 and 2, the mean square consensus of system (1) with controller (2) under the Markovian impulsive attacks can be reached if there exist symmetric positive definite matrix P and feedback gain K such that p λj υj
The sufficient conditions were derived with the help of some properties of the stochastic process, and some special cases with more or fewer assumptions were considered, including the determined, linear, and stationary processes

Summary

Introduction

With the development of hardware equipment and communication technology, the collaborative control problem has recently become the focus of studies of complex systems [1,2,3]. The consensus of multi-agent systems (MASs) plays an important role in the field of collective behaviors, owing to its excellent model assumptions and extensive application scenarios such as control of the formation of unmanned aerial vehicles [4], restoration of a power system [5], intelligent and sustainable supplier selection of supply chains [6], etc. In real-world application scenarios, communication among agents may be affected by the environment or various attacks, especially human-made malicious attacks, which is likely to cause the system to become unstable. Generally speaking, they may be classified into two main categories: denial-of-service (DoS) attacks [7,8,9,10]. In the above research, the results were based on a linear or an additive assumption and assumptions on the attack model were made, resulting in narrow scopes of applications

Objectives

Results

Conclusion