Multi‐tracking control of heterogeneous multi‐agent systems with single‐input– single‐output based on complex frequency domain analysis

Zhang, Wenle; Liu, Jianchang; Wang, Honghai

doi:10.1049/iet-cta.2015.1184

Cited by 15 publications

(6 citation statements)

References 20 publications

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“…Hu and Guan (2016) adopt a node clustering scheme to ensure a relatively high degree of connectivity within each potential subgroup and use some exclusion effects to deal with subgroup outbound links. Zhang, Liu, and Wang (2016) convert the multi-tracking control problem of MASs into the zero-stationary error control problem of some independent subsystems and study the multitracking control of high-order heterogeneous MASs. Yan and Yu (2017) study event-triggered tracking control of a coupled-group MASs.…”

Section: Multi-consensus and Multi-trackingmentioning

confidence: 99%

A survey of the consensus for multi-agent systems

Tan

2019

Systems Science & Control Engineering

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Multi-agent systems (MASs) has developed into an emerging complex system science and gradually infiltrated into various fields of social life. The problem of consensus (i.e. all agents eventually to reach an agreement upon a common quantity of interest) is the basis of distributed coordinated control of the MASs, which has attracted tremendous attention from both theoretical and practical perspectives. This paper comprehensively reviews the state-of-the-art development in the consensus of MASs. Firstly, the basic framework and overview of MASs and consensus are discussed. Secondly, the motivations, results and methods of several kinds of consensus problems are introduced, including consensus subjected to communication constraints, leader-following consensus, group consensus, consensus based on trigger mechanism, finite-time consensus, multi-consensus and multi-tracking. Finally, some challenging issues and development trends of the consensus of MASs are considered.

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Section: Multi-consensus and Multi-trackingmentioning

confidence: 99%

A survey of the consensus for multi-agent systems

Tan

2019

Systems Science & Control Engineering

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“…In this paper, the followers' input are quantized by the newly proposed adaptive dynamic quantizer, which solve the problem leader-following consensus with limited communication bandwidth. The static quantizer in [30] is a special case of the newly proposed dynamic quantizer, the dynamic gain parameter is 1 and applied to the SISO system [31].…”

Section: Introductionmentioning

confidence: 99%

Distributed Control for Leader-Following Consensus Problem of Second-Order Multi-Agent Systems and Its Application to Motion Synchronization

Shi

Hou

2019

Applied Sciences

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This paper solves the leader-following consensus problem for a class of second-order multi-agent systems with input quantized by a newly proposed adaptive dynamic quantizer. The novel dynamic quantizer is an adaptive quantizer that combines the logarithmic quantizer and the uniform quantizer by introducing dynamic gain parameters to achieve quantizer adaptive adjustment. It has advantages of logarithmic, uniform, and adaptive dynamic quantizers in ensuring reducible communication expenses and acceptable quantizer errors for better system performance. On this basis, we transform the guide way climbing frame (GWCF) under ideal conditions into a second-order multi-agent system and solve the motion synchronization problem of GWCF. Finally, we illustrate our approach by numerical examples.

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“…Further development on the analytical design methods of control for the general integrator multi‐agent systems is desirable and valuable. Considering the linear system dynamics in consensus, frequency‐domain approach is a powerful tool for stability analysis of the closed‐loop systems [15, 16]. Initially, Gattami and Murray [17] presented a general frequency domain model and a Nyquist‐like criterion to study the consensus problem.…”

Section: Introductionmentioning

confidence: 99%