H consensus control of discrete-time multi-agent systems under network imperfections and external disturbance

Elahi, Arezou; Alfi, Alireza; Modares, Hamidreza

doi:10.1109/jas.2019.1911474

Cited by 52 publications

(3 citation statements)

References 34 publications

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“…Leader-following consensus of MAS (38) with external disturbance d i (t) is transformed into the robust H ∞ -control of the tracking error system. Under the model-based STC scheme (3) and ( 42), the following modelbased H ∞ stability condition comes ready whose proof is similar to that of the model-based approach in [41] and is thus omitted here.…”

Section: Comparison With the Model-based Stcmentioning

confidence: 99%

Data-driven consensus control of fully distributed event-triggered multi-agent systems

Wang

Sun

et al. 2023

Sci. China Inf. Sci.

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This paper considers self-triggered consensus control of unknown linear multi-agent systems (MASs). Selftriggering mechanisms (STMs) are widely used in MASs, thanks to their advantages in avoiding continuous monitoring and saving computing and communication resources. However, existing results require the knowledge of system matrices, which are difficult to obtain in real-world settings. To address this challenge, we present a data-driven approach to designing STMs for unknown MASs building upon the model-based solutions. Our approach leverages a system lifting method, which allows us to derive a data-driven representation for the MAS. Subsequently, a datadriven self-triggered consensus control (STC) scheme is designed, which combines a data-driven STM with a state feedback control law. We establish a data-based stability criterion for asymptotic consensus of the closed-loop MAS in terms of linear matrix inequalities, whose solution provides a matrix for the STM as well as a stabilizing controller gain. In the presence of external disturbances, a model-based STC scheme is put forth for H∞consensus of MASs, serving as a baseline for the data-driven STC. Numerical tests are conducted to validate the correctness of the data-and model-based STC approaches. Our data-driven approach demonstrates a superior trade-off between control performance and communication efficiency from finite, noisy data relative to the system identification-based one.

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Section: Comparison With the Model-based Stcmentioning

confidence: 99%

Data-driven consensus control of fully distributed event-triggered multi-agent systems

Wang

Sun

et al. 2023

Sci. China Inf. Sci.

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“…Through the establishment of Lyapunov functionals for time‐delay multiagent networks, the sufficient condition was provided in Reference 20 to guarantee the leader‐following consensus. For the multiagent networks possessed disturbances and communication delay, a sufficient condition based on the form of linear matrix inequalities was offered in Reference 21 to assure the

{H}_{\infty }

consensus. By dint of the established predictor feedback protocol, the output consensus problem was investigated in Reference 22 for multiagent networks in the present of the different type delays 23 .…”

Section: Introductionmentioning

confidence: 99%

Discrete time‐delay multiagent networks: Pseudo‐predictor, full‐order, and reduced‐order observer

Liu

Chai

2022

Intl J Robust & Nonlinear

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This article studies the consensus and the input delay compensation problems for discrete-time linear multiagent networks with time delays in the state and input. Pseudo-predictor feedback (PPF) protocol is proposed, which makes use of the artificial closed-loop dynamics to predict the future states. Sufficient conditions are offered to guarantee the multiagent consensus on the grounds of the stability of difference equations. Full-order observer based PPF protocol and reduced-order observer based PPF protocol are simultaneously established, and it is revealed that, under the PPF protocol, the convergence rate of the states is fastest. Compared with the existent predictor feedback protocol, the proposed protocol greatly reduces the calculation burden and is easier to implement since it has no concern with the (history) input information. Finally, a numerical example is carried out to demonstrate the effectiveness of the proposed protocols.

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“…In addition to overflow nonlinearities and state-delay, external disturbance is also experienced in the discrete-time systems. The analysis of systems with external disturbances is an important research topic due to its wide applications, and it continues to attract many researchers (Elahi et al, 2019; Xia et al, 2010; Zhang et al, 2007). The disturbance is inevitable in the higher order digital filters when implemented using lower order digital filters.…”

Section: Introductionmentioning

confidence: 99%

Stability of state-delayed digital filters with overflow nonlinearities

Parthipan

Kokil

2021

Transactions of the Institute of Measurement and Control

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In this work, stability of digital filters in the presence of overflow nonlinearities and time-varying delay is investigated with/without external disturbance. Two new lemmas related to characterization of overflow nonlinearities are developed. The first lemma is established with better utilization of system information which includes overflow nonlinearities, previous and current states of the digital filter. The second lemma associated with overflow nonlinearities is developed with lesser constraints. Furthermore, by utilizing the established lemmas and a new Lyapunov functional, an asymptotic stability condition is presented for the digital filter with time-varying delay and overflow nonlinearities. The developed condition is shown to be more relaxed and computationally less demanding than the existing criteria. In addition to that, a sufficient condition is derived under which the digital filter with external disturbance, overflow nonlinearities, and time-varying delay has a prescribed noise attenuation level. To show the efficacy of the proposed approach, numerical examples are presented.

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H consensus control of discrete-time multi-agent systems under network imperfections and external disturbance

Cited by 52 publications

References 34 publications

Data-driven consensus control of fully distributed event-triggered multi-agent systems

Data-driven consensus control of fully distributed event-triggered multi-agent systems

Discrete time‐delay multiagent networks: Pseudo‐predictor, full‐order, and reduced‐order observer

Stability of state-delayed digital filters with overflow nonlinearities

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