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Attack-Resilient Lateral Stability Control for Autonomous In-Wheel-Motor-Driven Electric Vehicles

机译:自主轮式电动机驱动电动车辆的攻击弹性横向稳定性控制

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This paper presents an attack-resilient lateral stability control design approach for autonomous in-wheel-motor-driven electric vehicles (EVs) to enhance the cyber-physical security of the steering system. Specifically, this work examines cyber-attacks on the steering angle, one of the most safety-critical control signals in autonomous driving systems. Different from the current literature, the proposed system serves as an assistant controller in the monitoring system. Once a cyber-attack is identified, a disturbance estimator is then designed based on the lateral system dynamics, which models cyber-attacks as an exogenous disturbance. Then, a robust predictive controller is developed to mitigate the impact of cyber-attacks and ensure driving safety. The proposed attack-resilient control carries a low computational burden, making it applicable for real-time applications. Simulation results are finally provided to demonstrate the effectiveness of the proposed method.
机译:本文介绍了一种攻击弹性横向稳定性控制设计方法,用于自主轮式电动机驱动的电动车辆(EVS),以增强转向系统的网络物理安全性。 具体而言,这项工作检查了对转向角的网络攻击,自主驱动系统中最安全关键控制信号之一。 不同于当前文献,所提出的系统用作监控系统中的助理控制器。 一旦确定了网络攻击,那么基于横向系统动态设计干扰估计器,这些动态模拟网络攻击作为外源干扰。 然后,开发了一种强大的预测控制器来减轻网络攻击的影响并确保驾驶安全性。 所提出的攻击弹性控制具有低计算负担,适用于实时应用。 最后提供了仿真结果以证明所提出的方法的有效性。

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