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

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.

Authors

Institutions

Publication Details

Journal
Advanced Theory and Simulations
Published
2025-01-10
DOI
https://doi.org/10.1002/adts.202401247
Citations
2
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
2.97

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Jiale Zhang, Gaoqi Lian, Shengjie Jiao, Wei Meng et al.
2 citations
Advanced Theory and Simulations
Distributed Control Multi-Agent Systems
2.97
article

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

Jiale Zhang, Gaoqi Lian, Shengjie Jiao, Wei Meng, Chuanwei Zhang, Peilin Qin
article en
2 citations

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.

Advanced Theory and SimulationsVol. 8(4)
Xi'an University of Science and Technology (CN), National University of Singapore (SG), Chang'an University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Sustainable cities and communities
Openalex Percentile: Top 11%
Distributed Control Multi-Agent Systems
2.97
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.