Funnel-Based Adaptive Optimal Resilient Control for Air–Ground Cooperative Systems With Composite Disturbances
针对空地协同系统受虚假数据注入攻击和复合扰动的问题，提出一种基于漏斗边界和复合扰动观测器的自适应神经网络最优弹性控制策略，确保编队跟踪稳定且性能优化。
This article addresses the adaptive neural network-based optimal resilient control problem for a class of air–ground cooperative systems subject to the false data injection (FDI) attacks and the composite disturbances. First, a novel funnel boundary is designed to constrain formation errors with prescribed transient and steady-state performance, ensuring collision avoidance. Second, a composite disturbance observer (CDO) is proposed to accurately estimate and compensate for both external and neighbor-induced coupled disturbances. Furthermore, an optimal resilient control strategy is formulated within a backstepping framework with an actor–critic neural network (NN) to mitigate FDI attacks, ensuring stable formation tracking and performance optimization. The theoretical analysis proves the boundedness of all closed-loop signals and the convergence of formation errors within the funnel. The numerical simulations validate the approach’s effectiveness and superiority.