Event-Triggered Fixed-Time Consensus Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Dead-Zone Input

This study explores the issue of fixed-time dynamic event-triggered consensus control for uncertain nonlinear multi-agent systems (MASs) within directed graph frameworks. In practical applications, the system encounters multiple constraints such as unknown time-varying parameters, unknown external disturbances, and input dead zones, which may increase the communication burden of the system. Therefore, achieving fixed-time consensus tracking control under the aforementioned conditions is challenging. To address these issues, an adaptive fixed-time consensus tracking control method based on boundary estimation and fuzzy logic systems (FLSs) is proposed to achieve online compensation for the input dead zone. Additionally, to optimize the utilization of communication resources, a periodic adaptive event-triggered control (PAETC) is designed. The mechanism dynamically adjusts the frequency at which the trigger is updated in real time, reducing communication resource usage by responding to changes in the control signal. Finally, the efficacy of the proposed approach is confirmed via theoretical evaluation and simulation.

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Publication Details

Journal
Actuators
Published
2025-08-22
DOI
https://doi.org/10.3390/act14090414
Primary Topic
Neural Networks Stability and Synchronization
Type
article
Field-Weighted Citation Impact
0.00
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article

Event-Triggered Fixed-Time Consensus Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Dead-Zone Input

Jietao Dai, Zian Wang, Kai Feng, Jiarui Liu et al.
Actuators
Neural Networks Stability and Synchronization
article

Event-Triggered Fixed-Time Consensus Tracking Control for Uncertain Nonlinear Multi-Agent Systems with Dead-Zone Input

Jietao Dai, Zian Wang, Kai Feng, Jiarui Liu, Yue Zhang, Yixiang Gu, Guan Zheng
article en

Abstract

This study explores the issue of fixed-time dynamic event-triggered consensus control for uncertain nonlinear multi-agent systems (MASs) within directed graph frameworks. In practical applications, the system encounters multiple constraints such as unknown time-varying parameters, unknown external disturbances, and input dead zones, which may increase the communication burden of the system. Therefore, achieving fixed-time consensus tracking control under the aforementioned conditions is challenging. To address these issues, an adaptive fixed-time consensus tracking control method based on boundary estimation and fuzzy logic systems (FLSs) is proposed to achieve online compensation for the input dead zone. Additionally, to optimize the utilization of communication resources, a periodic adaptive event-triggered control (PAETC) is designed. The mechanism dynamically adjusts the frequency at which the trigger is updated in real time, reducing communication resource usage by responding to changes in the control signal. Finally, the efficacy of the proposed approach is confirmed via theoretical evaluation and simulation.

ActuatorsVol. 14(9)
Guangzhou University (CN)
Decent work and economic growth
Openalex Percentile: Top 76%
Neural Networks Stability and Synchronization
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