Secure Consensus Control for Constrained Multi-Agent Systems Against Intermittent Denial-of-Service Attacks: An Adaptive Dynamic Programming Method

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.