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

Jiale Zhang, Chuanwei Zhang, Shengjie Jiao, Peilin Qin, Wei Meng, Gaoqi Lian

Year
2025
Citations
2

Abstract

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.

Keywords

Dead zoneLeakage (economics)RobotControl theory (sociology)Computer scienceArtificial intelligenceControl (management)BiologyEconomicsEcology

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