An Operator-Theoretic Approach to Robust Event-Triggered Control of Network Systems With Frequency-Domain Uncertainties

被引:1
|
作者
Zhang, Shiqi [1 ]
Lv, Yuezu [2 ]
Li, Zhongkui [1 ]
机构
[1] Peking Univ, Coll Engn, Dept Mech & Engn Sci, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
[2] Beijing Inst Technol, Adv Res Inst Multidisciplinary Sci, Beijing 100081, Peoples R China
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Uncertainty; Frequency-domain analysis; Robustness; Heuristic algorithms; Time-domain analysis; Network systems; Laplace equations; Distributed control; event-triggered control; frequency-domain uncertainties; operator theory; robust control; DYNAMIC AVERAGE CONSENSUS; MULTIAGENT SYSTEMS; SYNCHRONIZATION; STABILITY;
D O I
10.1109/TAC.2022.3169880
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we study the robustness of the event-triggered consensus algorithms against frequency-domain uncertainties. It is revealed that the sampling errors resulted by event triggering are essentially images of linear finite-gain $\mathcal {L}_{2}$-stable operators acting on the consensus errors of the sampled states and the event-triggered mechanism is equivalent to a negative feedback loop introduced additionally to the feedback system. In virtue of this, the robust consensus problems of the event-triggered network systems subject to additive dynamic uncertainties and network multiplicative uncertainties are considered, respectively. In both cases, quantitative relationships among the parameters of the controllers, the Laplacian matrix of the network topology, and the robustness against aperiodic event triggering and frequency-domain uncertainties are unveiled. Furthermore, the event-triggered dynamic average consensus (DAC) problem is also investigated, wherein the sampling errors are shown to be images of nonlinear finite-gain operators. The robust performance of the proposed DAC algorithm is analyzed, which indicates that the robustness and the performance are negatively related to the eigenratio of the Laplacian matrix. Simulation examples are also provided to verify the obtained results.
引用
收藏
页码:2034 / 2047
页数:14
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