首页|Fixed-time adaptive consistent control of higher-order nonlinear multi-agent systems with full state constraints and input saturation

Fixed-time adaptive consistent control of higher-order nonlinear multi-agent systems with full state constraints and input saturation

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This paper investigates high-order nonlinear multi-agent systems with state constraints and input saturation. A novel control scheme incorporating Neural Networks and Barrier Lyapunov Functions is designed to achieve adaptive fixed-time consensus control. This innovative scheme effectively addresses the complexity explosion problem typical in traditional controller designs while ensuring that the closed-loop system remains within its constraints. During the design process, a first-order sliding mode differentiator was introduced, and compensations were made for filter errors to ensure stability and consistency within a fixed-time. Additionally, experiments using Matlab numerical simulations and the StarSim semi-physical simulation platform confirm that the proposed control scheme significantly surpasses traditional methods in efficiency and accuracy, validating its effectiveness and practicality for solving the consensus problem in high-order nonlinear multi-agent systems.

Barrier Lyapunov functionInput saturatedMulti-agent systemsFixed-time controlCONSENSUS TRACKING CONTROLDYNAMIC SURFACE CONTROLDESIGN

Zhu, Guoqiang、Zhang, Xuecheng、Zhang, Xiuyu、Su, Chun-Yi

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Northeast Elect Power Univ||Jilin Prov Int Res Ctr Precis Drive & Intelligent

Concordia Univ

2025

Neurocomputing

Neurocomputing

SCI
ISSN:0925-2312
年,卷(期):2025.639(Jul.28)
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