Adaptive Robust Formation Tracking Control for Traffic Cone Robots Under Uncertain Disturbances: With Leakage and Dead Zone Types

IF 2.9 4区 工程技术 Q1 MULTIDISCIPLINARY SCIENCES
Jiale Zhang, Chuanwei Zhang, Shengjie Jiao, Peilin Qin, Meng Wei, Gaoqi Lian
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引用次数: 0

Abstract

Traffic cones, as indispensable safety facilities for road maintenance, play a crucial role in directing traffic flow and ensuring construction safety. This study addresses the challenge of adaptive robust formation tracking control for uncertain traffic cone robots (TCRs). Based on the Udwadia–Kalaba method, the kinematic constraints of the TCRs are designed by the artificial potential function. Those constraints are considered as the control objectives realized by robust control. The uncertainty of the TCRs in this study includes matching and mismatching components. To address matching uncertainties, adaptive parameters incorporating dead-zone and leakage terms are introduced, enabling precise real-time estimation of uncertainty dynamics. For mismatching uncertainties, a geometric decomposition approach is employed, effectively isolating them in a subspace orthogonal to the formation tracking range space. The proposed system is validated through extensive simulations and real-world experiments, demonstrating its robustness and practical effectiveness in addressing the stated challenges.

Abstract Image

不确定干扰下交通锥机器人的自适应鲁棒编队跟踪控制:带泄漏和死区类型
交通锥作为道路养护不可缺少的安全设施,在引导交通流量、保障施工安全方面发挥着至关重要的作用。针对不确定交通锥机器人(tcr)的自适应鲁棒队列跟踪控制问题进行了研究。基于Udwadia-Kalaba方法,利用人工势函数设计了tcr的运动约束。将这些约束条件作为鲁棒控制实现的控制目标。本研究中tcr的不确定度包括匹配和不匹配成分。为了解决匹配的不确定性,引入了包含死区和泄漏项的自适应参数,实现了不确定性动态的精确实时估计。对于不匹配的不确定性,采用几何分解方法,有效地将其隔离在与地层跟踪距离空间正交的子空间中。通过大量的仿真和真实世界的实验验证了所提出的系统,证明了它在解决所述挑战方面的鲁棒性和实际有效性。
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来源期刊
Advanced Theory and Simulations
Advanced Theory and Simulations Multidisciplinary-Multidisciplinary
CiteScore
5.50
自引率
3.00%
发文量
221
期刊介绍: Advanced Theory and Simulations is an interdisciplinary, international, English-language journal that publishes high-quality scientific results focusing on the development and application of theoretical methods, modeling and simulation approaches in all natural science and medicine areas, including: materials, chemistry, condensed matter physics engineering, energy life science, biology, medicine atmospheric/environmental science, climate science planetary science, astronomy, cosmology method development, numerical methods, statistics
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