Fully Distributed Consensus of Multiple Euler–Lagrange Systems With Time-Varying Asymmetric Full-State Constraints

In this article, the consensus problem of multiple Euler–Lagrange (EL) systems with time-varying asymmetric full-state constraints under a directed graph is investigated in a fully distributed way, where the global information dependence is removed. First, to prevent the violation of the full-state constraints of each EL system, a nonlinear state-dependent transformation is adopted for both the leader and followers, where the constraints will not be violated as long as the transformed states remain finite. Then, a constrained nonlinear fully distributed observer is constructed using only neighbors' states, and an adaptive gain is designed to eliminate the dependence of the global information. The theoretical analysis is completed via constructing a novel integration-based Lyapunov function using a graph-based diagonal matrix, ensuring the achievement of consensus. Using the observed state, an adaptive backstepping state tracking control protocol is developed such that the position of each EL system can track the leader within a tolerable bounded region. Thus, the leader-following consensus of multiple EL systems with time-varying asymmetric full-state constraints is achieved. Simulation results are illustrated to show the feasibility and effectiveness of the proposed control scheme.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-02-26
DOI
https://doi.org/10.1109/tac.2025.3546080
Citations
4
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
5.95

Funders

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

Fully Distributed Consensus of Multiple Euler–Lagrange Systems With Time-Varying Asymmetric Full-State Constraints

Yanhua Yang, Jie Mei, Guangfu Ma, Xiongtao Shi
4 citations
IEEE Transactions on Automatic Control
Distributed Control Multi-Agent Systems
5.95
article

Fully Distributed Consensus of Multiple Euler–Lagrange Systems With Time-Varying Asymmetric Full-State Constraints

Yanhua Yang, Jie Mei, Guangfu Ma, Xiongtao Shi
article en
4 citations

Abstract

In this article, the consensus problem of multiple Euler–Lagrange (EL) systems with time-varying asymmetric full-state constraints under a directed graph is investigated in a fully distributed way, where the global information dependence is removed. First, to prevent the violation of the full-state constraints of each EL system, a nonlinear state-dependent transformation is adopted for both the leader and followers, where the constraints will not be violated as long as the transformed states remain finite. Then, a constrained nonlinear fully distributed observer is constructed using only neighbors' states, and an adaptive gain is designed to eliminate the dependence of the global information. The theoretical analysis is completed via constructing a novel integration-based Lyapunov function using a graph-based diagonal matrix, ensuring the achievement of consensus. Using the observed state, an adaptive backstepping state tracking control protocol is developed such that the position of each EL system can track the leader within a tolerable bounded region. Thus, the leader-following consensus of multiple EL systems with time-varying asymmetric full-state constraints is achieved. Simulation results are illustrated to show the feasibility and effectiveness of the proposed control scheme.

IEEE Transactions on Automatic ControlVol. 70(8)
Harbin Institute of Technology (CN), Guangdong Institute of Intelligent Manufacturing (CN)
National Natural Science Foundation of China, Shenzhen Fundamental Research Program, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 4%
Distributed Control Multi-Agent Systems
5.95
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.