This paper studied the group consensus problem in heterogeneous multi-agent systems (HMASs) subject to input delays, denial of service (DoS) attacks, and external disturbances. The agents interact within a cooperative-competitive network, where first- and second-order dynamics coexist. To address the challenges introduced by disruptions in communication and system heterogeneity, an intermittent control protocol was designed. This protocol operates based on a time-varying binary signal that reflects the availability of communication. Control actions are suspended during DoS intervals and resume when communication is restored. The proposed method incorporates virtual velocity estimation to handle mixed-order agents and employs frequency-domain analysis, specifically the Nyquist stability criterion, to derive algebraic conditions that ensure consensus. These conditions relate the maximum allowable delay to system topology, attack patterns, and disturbance levels. Numerical simulations demonstrate that consensus can be achieved under both directed and undirected network structures, even in the presence of constrained DoS disruptions and bounded disturbances.

This article investigated the fuzzy adaptive fault-tolerant resilient formation control issue for uncertain nonlinear multi-agent systems (MASs) with immeasurable states and under denial-of-service (DoS) attacks. Fuzzy logic systems were utilized to model unknown agents, and a fuzzy state estimator was formulated to reconstruct the agents' unknown states. A distributed resilient formation estimator was proposed to obtain the unknown leader information estimation and its high-order derivatives under DoS attacks. Based on the designed fuzzy state and resilient formation estimators, a fault-tolerant fuzzy output-feedback adaptive resilient formation control scheme was developed via the backstepping control methodology. It was proven that the developed fault-tolerant fuzzy resilient formation control scheme can guarantee that the controlled nonlinear MASs were stable and formation tracking errors converged even under unknown states, actuator faults, and DoS attacks. Finally, the proposed fuzzy adaptive fault-tolerant resilient formation control method was applied to marine surface vehicles; the simulation results and comparisons showed the effectiveness of the presented control methodology.