Event-Triggered Mechanism Based Non-Fragile Consensus Control for Multi-Rate Multi-Agent Systems

Liu Jian-hua; Li Jia-hui; Liu Xiao-bin; Mu Shu-juan; Dong Hong-li

doi:10.12052/gdutxb.220066

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Event-Triggered Mechanism Based Non-Fragile Consensus Control for Multi-Rate Multi-Agent Systems

更新时间：2026-05-27

- Event-Triggered Mechanism Based Non-Fragile Consensus Control for Multi-Rate Multi-Agent Systems
- Vol. 39, Issue 5, Pages: 102-111(2022)
- 作者机构：
  
  1. 东北石油大学人工智能能源研究院,黑龙江,大庆,163318
  2. 东北石油大学黑龙江省网络化与智能控制重点实验室,黑龙江,大庆,163318
  3. 东北石油大学三亚海洋油气研究院,海南,三亚,572024
  4. 上海电子信息职业技术学院中德工程学院,上海,201411
- 作者简介：
- 基金信息：
- DOI：10.12052/gdutxb.220066
  CLC： TP273
- Published：2022
- 稿件说明：
移动端阅览
刘建华, 李佳慧, 刘小斌, 穆树娟, 董宏丽. 事件触发机制下的多速率多智能体系统非脆弱一致性控制[J]. 广东工业大学学报, 2022, 39(5): 102-111.

Liu Jian-hua, Li Jia-hui, Liu Xiao-bin, et al. Event-Triggered Mechanism Based Non-Fragile Consensus Control for Multi-Rate Multi-Agent Systems[J]. 2022, 39(5): 102-111.
刘建华, 李佳慧, 刘小斌, 穆树娟, 董宏丽. 事件触发机制下的多速率多智能体系统非脆弱一致性控制[J]. 广东工业大学学报, 2022, 39(5): 102-111. DOI： 10.12052/gdutxb.220066.

Liu Jian-hua, Li Jia-hui, Liu Xiao-bin, et al. Event-Triggered Mechanism Based Non-Fragile Consensus Control for Multi-Rate Multi-Agent Systems[J]. 2022, 39(5): 102-111. DOI： 10.12052/gdutxb.220066.

摘要

针对一类多速率多智能体系统，研究在事件触发机制下的非脆弱

∞

一致性控制问题。为了更符合实际需要，采用多速率采样策略，并通过提升技术将多速率采样转化为单速率采样。考虑到智能体间的通信负担，引入事件触发机制来减少智能体间的通信次数。此外，考虑到控制器在执行过程中可能出现的不精确性，本文设计一种可以容忍执行过程中变化/波动的控制器。综上，本文的目的是设计一种基于观测器的事件触发非脆弱控制器来实现多智能体系统的

∞

一致性控制。利用线性矩阵不等式技术，得到使系统满足

∞

一致性控制的充分条件，然后设计控制器参数。最后，为了说明事件触发控制方法的有效性，给出一个数值仿真实例。

Abstract

The research on the non-fragile

∞

-consensus control problem for a class of multi-rate multi-agent system under the event-triggered (ET) mechanism is focused on. In order to be more in line with actual need

a multi-rate sampling strategy is adopted

which leads to a multi-rate sampling that can be converted into a single-rate sampling via lifting technique. Considering the transmission burden among the agents

an ET mechanism is introduced to reduce the numbers of transmission among the agents. In addition

in view of the possible inaccuracy of the controller implementation

a controller that can tolerate the changes/fluctuations du

ring the implementation is designed to make the multi-agent system more robust. An observer-based ET non-fragile controller is designed to achieve the

∞

-consensus control of the multi-agent system

in which the controller can tolerate the variations/fluctuations during the implementation. By using the linear matrix inequality technique

the sufficient conditions are obtained that can ensure the

∞

-consensus control of the considered system

and then the controller parameters are designed. Finally

a numerical simulation example is given to prove the effectiveness of the ET control method.

关键词

Keywords

references

DU H, WEN G, WU D, et al . Distributed fixed-time consensus for nonlinear heterogeneous multi-agent systems [J ] . Automatica, 2020, 113: 108797.

ZOU W, SHI P, XIANG Z, et al . Finite-time consensus of second-order switched nonlinear multi-agent systems [J ] . IEEE Transac tions on Neural Networks and Learning Systems, 2019, 31(5): 1757-1762.

DUNBAR W B. Distributed receding horizon control of dynamically coupled nonlinear systems [J]. IEEE Transactions on Automatic Control, 2007, 52(7): 1249-1263.

FRANCO E, MAGNI L, PARISINI T, et al . Cooperative constrained control of distributed agents with nonlinear dynamics and delayed information exchange: a stabilizing receding-horizon approach [J ] . IEEE Transactions on Automatic Control, 2008, 53(1): 324-338.

LIN P, JIA Y, LI L. Distributed robust H ∞ consensus control in directed networks of agents with time-delay [J ] . Systems Control Letters, 2008, 57(8): 643-653.

WANG J, DUAN Z, WEN G, et al . Distributed robust control of uncertain linear multi-agent systems [J ] . International Journal of Robust and Nonlinear Control, 2015, 25(13): 2162-2179.

XU W, WANG Z, HO D W C. Finite-horizon H ∞ consensus for multiagent systems with redundant channels via an observer-type event-triggered scheme [J ] . IEEE Transactions on Cybernetics, 2017, 48(5): 1567-1576.

ZHAO Y, DUAN Z, WEN G, et al . Distributed H ∞ consensus of multi-agent systems: a performance region-based approach [J ] . International Journal of Control, 2012, 85(3): 332-341.

SAKTHIVEL R, KANAKALAKSHMI S, KAVIARASAN B, et al . Finite-time consensus of input delayed multi-agent systems via non-fragile controller subject to switching topology [J ] . Neurocomputing, 2019, 325: 225-233.

BAO H, PARK J H, CAO J. Non-fragile state estimation for fractional-order delayed memristive BAM neural networks [J]. Neural Networks, 2019, 119: 190-199.

JIANG X, XIA G, FENG Z. Non-fragile consensus control for singular multi-agent systems with Lipschitz nonlinear dynamics [J]. Neurocomputing, 2019, 351: 123-133.

WANG Z, DING D, SHU H. Non-fragile H ∞ control with randomly occurring gain variations, distributed delays and channel fadings [J ] . IET Control Theory Applications, 2015, 9(2): 222-231.

MA L, WANG Z, LAM H K. Mean-square H ∞ consensus control for a class of nonlinear time-varying stochastic multiagent systems: the finite-horizon case [J ] . IEEE Transactions on Systems, Man, and Cybernetics:Systems, 2016, 47(7): 1050-1 060.

BU X, DONG H, WANG Z, et al . Non-fragile distributed fault estimation for a class of nonlinear time-varying systems over sensor networks: the finite-horizon case [J ] . IEEE Transactions on Signal and Information Processing over Networks, 2018, 5(1): 61-69.

LI J, DONG H, LIU H, et al . Sampled-data non-fragile state estimation for delayed genetic regulatory networks under stochastically switching sampling periods [J ] . Neurocomputing, 2021, 463: 168-176.

LIU L, MA L, ZHANG J, et al . Distributed non-fragile set-membership filtering for nonlinear systems under fading channels and bias injection attacks [J ] . International Journal of Systems Science, 2021, 52(6): 1192-1205.

GENG H, LIANG Y, LIU Y, et al . Bias estimation for asynchronous multi-rate multi-sensor fusion with unknown inputs [J ] . Information Fusion, 2018, 39: 139-153.

QU B, WANG Z, SHEN B. Fusion estimation for a class of multi-rate power systems with randomly occurring SCADA measurement delays [J]. Automatica, 2021, 125: 109408.

HUA C, GE C, GUAN X. Synchronization of chaotic Lur’e systems with time delays using sampled-data control [J]. IEEE Transactions on Neural Networks and Learning Systems, 2014, 26(6): 1214-1221.

SHEN Y, WANG Z, DONG H, et al. Multi-sensor multi-rate fusion estimation for networked systems: advances and perspectives[J]. Information Fusion, 2022, 82: 19-27.

MA W W, JIA X C, ZHANG D W. Observer-based networked H ∞ control for dualrate sampling systems [J ] . Acta Automatica Sinica, 2015, 41(10): 1788-1797.

WEI G, WANG L, LIU Y. H ∞ control for a class of multi-agent systems via a stochastic sampled-data method [J ] . IET Control Theory Applications, 2015, 9(14): 2057-2065.

JU Y, TIAN X, LIU H, et al . Fault detection of networked dynamical systems: a survey of trends and techniques [J ] . International Journal of Systems Science, 2021, 52(16): 3390-3409.

GUAN Z H, YANG C, HUANG J. Stabilization of networked control systems with short or long random delays: a new multirate method [J]. International Journal of Robust and Nonlinear Control, 2010, 20(16): 1802-1816.

MOARREF M, RODRIGUES L. Stability and stabilization of linear sampled-data systems with multi-rate samplers and time driven zero order holds [J]. Automatica, 2014, 50(10): 2685-2691.

OHSHIMA M, HASHIMOTO I, OHNO H, et al . Multirate multivariable model predictive control and its application to a polymerization reactor [J ] . International Journal of Control, 1994, 59(3): 731-742.

GENG H, LIANG Y, YANG F, et al . Model-reduced fault detection for multi-rate sensor fusion with unknown inputs [J ] . Information Fusion, 2017, 33: 1-14.

GENG H, LIANG Y, YANG F, et al . The joint optimal filtering and fault detection for multi-rate sensor fusion under unknown inputs [J ] . Information Fusion, 2016, 29: 57-67.

IZADI I, ZHAO Q, CHEN T. An H ∞ approach to fast rate fault detection for multirate sampled-data systems [J ] . Journal of Process Control, 2006, 16(6): 651-658.

ZHANG P, DING S X, WANG G Z, et al . Fault detection for multirate sampled-data systems with time delays [J ] . International Journal of Control, 2002, 75(18): 1457-1471.

ZHONG M, YE H, DING S X, et al . Observer-based fast rate fault detection for a class of multirate sampled-data systems [J ] . IEEE Transactions on Automatic Control, 2007, 52(3): 520-525.

ZHANG Y, WANG Z, ZOU L, et al . Fault detection filter design for networked multi-rate systems with fading measurements and randomly occurring faults [J ] . IET Control Theory Applications, 2016, 10(5): 573-581.

LIANG Y, CHEN T, PAN Q. Multi-rate optimal state estimation [J]. International Journal of Control, 2009, 82(11): 2059-2076.

YAN L, JIANG L, XIA Y, et al . State estimation and data fusion for multirate sensor networks [J ] . International Journal of Adaptive Control and Signal Processing, 2016, 30(1): 3-15.

ZHANG H, BASIN M V, SKLIAR M. It–Volterra optimal state estimation with continuous, multirate, randomly sampled, and delayed measurements [J]. IEEE Transactions on Automatic Control, 2007, 52(3): 401-416.

GENG H, LIANG Y, ZHANG X. Linear-minimum-mean-square-error observer for multi-rate sensor fusion with missing measurements [J]. IET Control Theory Applications, 2014, 8(14): 1375-1383.

ZOU L, WANG Z, HU J, et al . Communication-protocol-based analysis and synthesis of networked systems: progress, prospects and challenges [J ] . International Journal of Systems Science, 2021, 52(14): 3013-3034.

HU J, ZHANG H, LIU H, et al . A survey on sliding mode control for networked control systems [J ] . International Journal of Systems Science, 2021, 52(6): 1129-1147.

WEI G, LIU L, WANG L, et al . Event-triggered control for discrete-time systems with unknown nonlinearities: an interval observer-based approach [J ] . International Journal of Systems Science, 2020, 51(6): 1019-1031.

ZHANG P, YUAN Y, GUO L. Fault-tolerant optimal control for discrete-time nonlinear system subjected to input saturation: a dynamic event-triggered approach [J]. IEEE Transactions on Cybernetics, 2019, 51(6): 2956-2968.

SUN Y, DING D, DONG H, et al . Event-based resilient filtering for stochastic nonlinear systems via innovation constraints [J ] . Information Sciences, 2021, 546: 512-525.

HU J, WANG Z, ALSAADI F E, et al . Event-based filtering for time-varying nonline ar systems subject to multiple missing measurements with uncertain missing probabilities [J ] . Information Fusion, 2017, 38: 74-83.

DING D, WANG Z, HAN Q L. A set-membership approach to event-triggered filtering for general nonlinear systems over sensor networks [J]. IEEE Transactions on Automatic Control, 2019, 65(4): 1792-1799.

NOWZARI C, GARCIA E, CORTÉS J. Event-triggered communication and control of networked systems for multi-agent consensus [J]. Automatica, 2019, 105: 1-27.

ÅARZÉN K E. A simple event-based PID controller [J]. IFAC Proceedings Volumes, 1999, 32(2): 8687-8692.

BOYD S, EL GHAOUI L, FERON E, et al. Linear matrix inequalities in system and control theory[M]. Philadelphia: Society for Industrial and Applied Mathematics, 1994: 55-87.

HAN F, WEI G, DING D, et al . Finite-horizon H ∞ -consensus control for multi-agent systems with random parameters: the local condition case [J ] . Journal of the Franklin Institute, 2017, 354(14): 6078-6097.

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