Fuzzy-Model-Based Lateral Control for Networked Autonomous Vehicle Systems Under Hybrid Cyber-Attacks
针对非线性自动驾驶车辆在外部干扰和网络攻击、时延、带宽限制下平滑跟踪规划路径的问题，提出基于模糊模型的横向控制方案，并设计异步弹性事件触发机制和动态输出反馈控制器，保证系统全局指数稳定。
This article addresses the problem of lateral control problem for networked-based autonomous vehicle systems. A novel solution is presented for nonlinear autonomous vehicles to smoothly follow the planned path under external disturbances and network-induced issues, such as cyber-attacks, time delays, and limited bandwidths. First, a fuzzy-model-based system is established to represent the nonlinear networked vehicle systems subject to hybrid cyber-attacks. To reduce the network burden and effects of cyber-attacks, an asynchronous resilient event-triggered scheme (ETS) is proposed. A dynamic output-feedback control method is developed to address the underlying problem. Conditions are derived to obtain the output-feedback controller and resilient asynchronous ETS such that the closed-loop switched fuzzy system is globally exponentially stable. Examples are provided to demonstrate the effectiveness and merits of the proposed new control design techniques.