Event-triggered robust distributed output feedback model predictive control for nonlinear MASs against false data injection attacks

In this paper, an event-triggered distributed output feedback model predictive control scheme for the nonlinear disturbed multiagent systems with sensor-controller channel false data injection attacks is proposed. To provide valid system states to the controller in the event of cyber attacks, a robust multivariate observer is designed to realize the estimation and separation of uncompromised system states, false data injection attacks, and measurement disturbances, simultaneously. Based on these reconstructed signals and a newly-designed linear robustness constraint, the distributed predictive controller is established to achieve smooth cooperative stabilization among agents. Meanwhile, an event-triggered mechanism is applied to save computing resources, and it restricts the error of predictive states and estimated states to guarantee the feasibility of the optimization control problem. Theoretical analyses on robustness and security for the nonlinear multiagent systems under event-triggered distributed output feedback model predictive control are presented. Finally, a simulation on two pairs of one-link flexible joint manipulator systems verifies the theoretical results.