Constraint-following adaptive robust control for multi-vehicle system formation with collision avoidance

Gang Xiao, Jiawen Li, Qinwen Yang, Longjie Fan, Qin Liao, Jin Huang
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Abstract

For the formation on unstructured road with complex road conditions, the rationality of constraint design and uncertainty compensation seriously affect the connected and autonomous vehicle (CAV) system performance. The system constraints are studied for safe and efficient formation driving, and an adaptive robust formation control scheme is proposed. First, for the desired configuration and global collision avoidance, a series of equality and unilateral inequality constraints are designed for inter-vehicle spacing. Second, a constraint handling scheme is proposed based on the diffeomorphism method, adjustable transformation function, and bounded constraint. Third, (possibly fast) time-varying but bounded multi-source uncertainty is considered, and then a self-adjusting leakage-type adaptive law is proposed to estimate the integrated uncertainty bound online. Fourth, the performance measure β is defined to evaluate the constraint-following error, and an adaptive robust control is proposed. The effectiveness of the proposed control scheme is verified by simulation. The results show that the proposed control renders the error to be uniformly bounded and uniformly ultimately bounded. The CAV system approximately follows the constraints, regardless of the uncertainty.
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带碰撞规避功能的多车系统编队的约束跟踪自适应鲁棒控制
在路况复杂的非结构化道路上进行编队时,约束设计的合理性和不确定性补偿严重影响互联与自动驾驶汽车(CAV)系统的性能。为实现安全高效的编队行驶,对系统约束条件进行了研究,并提出了一种自适应鲁棒编队控制方案。首先,为实现理想配置和避免全局碰撞,设计了一系列车辆间距的相等和单边不等式约束。其次,提出了一种基于差分法、可调变换函数和有界约束的约束处理方案。第三,考虑了(可能快速)时变但有界的多源不确定性,然后提出了一种自调整泄漏型自适应法则,用于在线估计综合不确定性边界。第四,定义性能指标 β 以评估约束跟踪误差,并提出自适应鲁棒控制。通过仿真验证了所提控制方案的有效性。结果表明,所提出的控制使误差均匀有界且最终均匀有界。无论存在何种不确定性,CAV 系统都能近似地遵循约束条件。
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