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A robust fuzzy control approach for path-following control of autonomous vehicles

机译:自动车辆路径控制的强大模糊控制方法

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This paper presents a robust fuzzy control approach for the lateral path-following of autonomous road vehicles (ARVs). The dynamics of the ARV is estimated online thorough a new non-singleton fuzzy system based on the non-stationary fuzzy sets. The asymptotic stability of the proposed method is ensured, and the adaptation laws for the proposed fuzzy system are derived based on the Lyapunov stability theorem. The robustness of the proposed control method is verified for a vehicle system performing a double-lane-change maneuver at different forward speeds subjected to structured and unmodeled uncertainties and different disturbances. The effectiveness of the proposed approach is further investigated under different measurement noise levels. Based on the obtained results, it is concluded that the proposed control strategy can be effectively applied to the path-following task of ARVs under a wide range of operating conditions and external disturbances.
机译:本文介绍了自主公路车辆(ARV)的横向路径跟踪的强大模糊控制方法。 ARV的动态估计在线彻底是基于非静止模糊套的新非单片机模糊系统。 确保了所提出的方法的渐近稳定性,基于Lyapunov稳定性定理导出所提出的模糊系统的适应法。 验证了所提出的控制方法的鲁棒性,用于以不同的前向速度执行双线车道变化机动的车辆系统,经受结构化和未拼接的不确定性和不同干扰。 在不同的测量噪声水平下进一步研究了所提出的方法的有效性。 基于所得的结果,得出结论,在广泛的操作条件和外部干扰下,可以有效地将所提出的控制策略有效地应用于ARV的路径。

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