Fixed-Time Fuzzy Resilient Consensus Tracking of Nonlinear MASs Under DoS Attacks and Actuator Faults

This paper addresses the output feedback fixed-time consensus tracking problem for nonlinear multiagent systems (MASs) subject to aperiodic DoS attacks and actuator faults. Different from existing resilient control methods for MASs where the attackers only destroy the connectivity between agents, the sensor-to-controller communication channels of each agent are simultaneously blocked in this paper. To overcome these difficulties, we first propose a novel fixed-time stability criterion that incorporates the characteristics of DoS attacks. Then, a fuzzy state estimator is constructed to estimate the immeasurable states as well as compensate for the adverse impact of attacks. In addition, novel adaptive laws are developed to handle an infinite number of actuator failures by estimating the bounds of failure parameters. Based on the Lyapunov stability theory, a fixed-time output feedback resilient control strategy is designed to guarantee that consensus tracking can be achieved, while the boundedness of all closed-loop signals in the MAS is ensured. At last, simulation studies are performed to validate the performance of the designed control law.
Note to Practitioners
—Many real-world systems, including robotic systems, manipulator systems and intelligent vehicle systems, can be represented as strict-feedback MASs. Note that these systems are notably susceptible to network attacks and operational faults. Consequently, ensuring the continued functionality of controlled MASs with DoS attacks and actuator faults has emerged as a paramount research focus. Furthermore, in the context of systems necessitating high transient performance standards, the concept of fixed-time convergence holds practical significance. In light of the challenges posed by DoS attacks and actuator faults, a novel fixed-time fuzzy fault-tolerant resilient consensus tracking approach is designed for nonlinear MASs. The proposed control laws cater to practical MASs which are characterized in strict-feedback form subject to unknown nonlinearities. Preliminary simulation results indicate the feasibility and efficacy of our developed approach.