Finite-time Bipartite Synchronization of Homogeneous and Heterogeneous Multiple Agents with Input Saturation: A TVRE-Based Gain Approach

Pursuing faster convergence rates and smaller input magnitudes seem to be two conflicting goals in studying multiagent systems. To give a tradeoff between the two, this article focuses on the bipartite synchronization problems over signed topologies and aims to achieve finite-time control for general linear agents subject to input saturation constraints. First, this article considers homogeneous agents and presents a class of bipartite synchronization protocols with saturation constraint, which exploits the solution of the time-varying Riccati equation (TVRE) to design the control gain. Then, a time-varying parameter scheduler is tactically designed for TVRE and achieves finite-time bipartite synchronization. Note that the design uses the solution computed online and brings a bit of conservatism in determining the settling time. So, for heterogeneous agents, this article constructs a modified parameter scheduler computed off-line to reduce the conservatism. A class of finite-time bipartite synchronization generators and generator-based finite-time protocols are proposed. It shows that, in both designs, the control input subjects to the bound saturation during convergence even if the gain escapes to infinity towards the settling time. Moreover, the tradeoff among the finite convergence time, the saturation bound of the input, and the initial domain are analyzed explicitly in theory. Finally, two simulations verify the validity of the theoretical results.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Automatic Control
Published
2025-02-18
DOI
https://doi.org/10.1109/tac.2025.3543560
Citations
7
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
10.41

Funders

Controls
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article

Finite-time Bipartite Synchronization of Homogeneous and Heterogeneous Multiple Agents with Input Saturation: A TVRE-Based Gain Approach

Yongfang Liu, Yu Zhao, Yuan Zhou, Zhongkui Li
7 citations
IEEE Transactions on Automatic Control
Distributed Control Multi-Agent Systems
10.41
article

Finite-time Bipartite Synchronization of Homogeneous and Heterogeneous Multiple Agents with Input Saturation: A TVRE-Based Gain Approach

Yongfang Liu, Yu Zhao, Yuan Zhou, Zhongkui Li
article en
7 citations

Abstract

Pursuing faster convergence rates and smaller input magnitudes seem to be two conflicting goals in studying multiagent systems. To give a tradeoff between the two, this article focuses on the bipartite synchronization problems over signed topologies and aims to achieve finite-time control for general linear agents subject to input saturation constraints. First, this article considers homogeneous agents and presents a class of bipartite synchronization protocols with saturation constraint, which exploits the solution of the time-varying Riccati equation (TVRE) to design the control gain. Then, a time-varying parameter scheduler is tactically designed for TVRE and achieves finite-time bipartite synchronization. Note that the design uses the solution computed online and brings a bit of conservatism in determining the settling time. So, for heterogeneous agents, this article constructs a modified parameter scheduler computed off-line to reduce the conservatism. A class of finite-time bipartite synchronization generators and generator-based finite-time protocols are proposed. It shows that, in both designs, the control input subjects to the bound saturation during convergence even if the gain escapes to infinity towards the settling time. Moreover, the tradeoff among the finite convergence time, the saturation bound of the input, and the initial domain are analyzed explicitly in theory. Finally, two simulations verify the validity of the theoretical results.

IEEE Transactions on Automatic ControlVol. 70(7)
Hong Kong Polytechnic University (HK), Northwestern Polytechnical University (CN), Peking University (CN), State Key Laboratory of Turbulence and Complex Systems
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Distributed Control Multi-Agent Systems
10.41
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