Event-based multi-target enclosing control for multi-ASV systems under DoS attacks

Abstract

This paper investigates the issue of multi-target enclosing control for multi-ASV systems under periodic denial-of-service (DoS) attacks with limited energy. To be consistent with the actual task scenarios, the multi-ASV system is subjected to model uncertainties, unmeasured velocity state variables, limited power, mechanical wear, actuator saturation, and external disturbances in this paper. First, an NN-based state observer is designed to estimate the unmeasured velocity state variables based on the nonlinear function approximation by the radial basis function neural network (RBFNN). Next, an event-based sliding mode control protocol is proposed to mitigate the negative effects of DoS attacks launched by the targets. The multi-ASV system can achieve enclosing control while tracking the convex combination of the states of the targets. Besides, the energy consumption and mechanical wear are reduced by the designed dynamic event-triggered mechanism (DETM). In addition, a saturation function is utilized to restrict the control input. Finally, the stability of the closed-loop system is verified by Lyapunov analysis and simulation results.