This paper investigates the adaptive tracking control problem for a class of strict-feedback uncertain nonlinear multi-agent systems (MASs) with input dead zones under the simultaneous presence of deception attacks and denial-of-service (DoS) attacks. A distributed leader-state estimator based on sampled data with time delays is proposed to estimate the leader's state under DoS attacks. To overcome the nonexistence of higher-order derivatives of the leader's estimated state, a filter is proposed and implemented. Based on the attacked output signals, a fuzzy state observer is constructed to reconstruct the unmeasurable states of the system. A fuzzy adaptive dead-zone control scheme is designed based on the backstepping method to mitigate the adverse effects of DoS attacks, deception attacks, dead zones, and uncertain nonlinear dynamics, while enabling the system to achieve the tracking control objective. Through Lyapunov stability analysis, the proposed control scheme is proven to guarantee that all signals in the closed-loop system are bounded and the tracking error converges to a neighborhood around the origin. Finally, simulations are conducted to verify the effectiveness of the theoretical results.

In this paper, we consider the output feedback event-triggered tracking control problem for a class of switched nonlinear multi-agent systems (MASs) with sensor faults and state constraints. For unknown nonlinear functions in the system, fuzzy logic systems are used to approximate them. To address sensor faults, sensor error compensation coefficients are designed to compensate for the errors caused by sensor faults. Meanwhile, state observer is designed to estimate the unmeasurable states in the system, providing necessary information for control design. Based on directed switching networks containing a directed spanning tree, an event-triggered output feedback controller is designed to enable the MAS to track the leader agent. By constructing a suitable barrier Lyapunov function, the stability of the system is analyzed, and it is proved that the consensus tracking can be achieved without violating the state constraints, the uniform boundedness of all the closed-loop system signals is ensured and the Zeno behavior can be eliminated. Finally, the effectiveness of the proposed algorithm is verified through a simulation example.