Secure consensus control for constrained multi-agent systems against intermittent denial-of-service attacks: an adaptive dynamic programming method
Zhen Qing Gao, Ning Zhao, Guangdeng Zong, Xudong Zhao
Abstract
Combining the use of the adaptive dynamic programming method and optimized backstepping strategy, this paper focuses on the secure consensus problem for constrained nonlinear multi-agent systems (MASs) subject to denial-of-service (DoS) attacks and input delay. Since network channels between some agents often suffer from intrusions by attackers during data transmission, we consider information transfers in both attack-sleep and attack-active scenarios, and construct a novel distributed observer with a switched mechanism to estimate the leader’s state information. In order to optimize system performances while ensuring that the system states do not exceed constraint sets, a new performance index function and a tan-type barrier Lyapunov function (BLF) are introduced. Besides, by employing the Pade approximation and an intermediate variable, the effect of input delay is removed. As a consequence, the proposed optimal control can smoothly steer the nonlinear MASs to realize the followers-leader consensus tracking goal, and all system states are consistently constrained within their compact sets. Finally, simulation results verify the effectiveness of this control scheme.