Prescribed-Time Cooperative Resilient Fuzzy Control for CPVS Under DoS Attacks

In this paper, the prescribed-time cooperative resilient fuzzy tracking control problem is addressed for thirdorder nonlinear cyber-physical vehicle systems (CPVS) under denial-of-service (DoS) attacks. Different from the existing results on cooperative resilient fuzzy tracking control, the developed method can achieve the cooperative resilient fuzzy tracking control objective within the prescribed time. To begin with, a data-driven-based online learning algorithm is introduced for learning the unknown and switching matrix of the reference signal. Based on the learned matrix, novel distributed resilient cooperative observers are designed to achieve prescribed-time observation by introducing an asynchronous observing method. To further improve the smoothness of the observation signal, a new improved smooth second-order prescribed-time observer is designed. Furthermore, leveraging the states of the smooth observer, a fuzzy controller is proposed to achieve precise tracking within the prescribed time, independent of initial conditions using the scaling error method and the backstepping technique. Finally, a simulation example is included to illustrate the effectiveness of the proposed methodology