Resilient Distributed Cooperative Optimization for Cyber-Physical Vehicle Systems Under DoS Attacks

In this article, the resilient distributed cooperative optimization problem is investigated for cyber-physical vehicle systems (CPVSs) in the presence of denial-of-service (DoS) attacks. Unlike existing results on distributed cooperative optimization for CPVSs, a novel layered design approach is introduced, which consists of a resilient distributed optimization algorithm, low-pass filters, and adaptive fuzzy controller. In particular, a novel resilient distributed optimization algorithm is first designed to ensure convergence to the optimal solution in the presence of DoS attacks. Then, a novel third-differentiable variable is generated through the low-pass filters, which ensures the existence of the third-order time derivatives of the signal even under DoS attacks. In order to deal with situations where the states of vehicles involve both dynamic uncertainties and unknown nonlinearities, an adaptive controller is proposed based on the adaptive technique that enables the states of the vehicles to converge toward the optimal trajectory. A numerical simulation is finally presented to demonstrate the practical feasibility and performance of the proposed approach.