Consensus of linear multi‐agent systems subject to communication delays and switching networks

Lu, Maobin; Liu, Lu

doi:10.1002/rnc.3750

Cited by 23 publications

(6 citation statements)

References 31 publications

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“…As will be shown later, under Assumption , the solvability of Problem does not rely on Assumption . For the solvability of consensus problem, various assumptions are made on the connectivity of the graph . Assumption is a standard assumption on the leader‐following consensus problem .…”

Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Leader‐following consensus of multiple uncertain Euler‐Lagrange systems

Liu

2018

Intl J Robust & Nonlinear

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Summary A new adaptive distributed controller is developed for the leader‐following consensus problem of multiple uncertain Euler‐Lagrange systems. A distinct feature of our proposed approach as opposed to the existing ones is that it does not need the exchange of controller's state among the communication network. As a consequence, it not only makes the implementation of the controller much easier but also reduces the communication cost. The effectiveness of the main result is demonstrated by some exemplary applications to cooperative control of multiple two‐link robot arms.

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Section: Problem Formulation and Preliminariesmentioning

confidence: 99%

Leader‐following consensus of multiple uncertain Euler‐Lagrange systems

Liu

2018

Intl J Robust & Nonlinear

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“…But the cost is excluding a part of agents whose inputs cannot be decoupled. In addition, Scardovi and Sepulchre (2009), Lu and Liu (2017) have investigated the synchronization (consensus) of a network of linear agent systems. They have proposed dynamic controllers that decouple the interaction between dynamics of agents and network topologies so that dynamics can be transformed to the form of single-integrators, by which consensus can be ensured.…”

Section: Introductionmentioning

confidence: 99%

Consensus analysis of multi-agent systems with general linear dynamics and switching topologies by non-monotonically decreasing Lyapunov function

Zhang

Chen

2019

Systems Science & Control Engineering

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This paper investigates consensus problems for multi-agent systems with general linear dynamics and switching topologies. In order to deal with the intricate interaction between dynamics of isolated agents and switching-disconnected topologies, the consensus analysis is performed by nonmonotonically decreasing Lyapunov function. Particularly, the design of consensus laws is explored from the perspective of fast time-varying systems with two time scales. Sufficient conditions for achieving consensus are derived, which depend on not only feedback gains and connectivity of network topologies but also the speed of topology switching and the stability of individual agent. Therefore consensus laws are generalized in the sense that the dynamics of linear agents are allowed to be unstable and switching topologies are allowed to be jointly weakly connected and balanced. Finally, numerical simulations are provided to demonstrate the effectiveness of theoretical results. ARTICLE HISTORY

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“…Consensus means that the states of agents reach a common state through local neighbors information as time goes on. Consensus has become a hot topic, which has been researched from different perspectives based on the practical demands, for example, the consensus problem under different communication topologies: the fixed topology or switching topology [2,3]; the consensus problem under different dynamical structures, which include single-integrator dynamics or higher-integrator dynamics [4,5]; the consensus problem with time delay: input delay or communication delay [6,7]; the consensus problem with unknown factors or external disturbance [8,9]; the leaderless consensus or leader-follower consensus [7,10]; the group consensus problem [11]; and the design of control laws based on different control methods [12,13].…”

Section: Introductionmentioning

confidence: 99%

Neural Networks Based Adaptive Consensus for a Class of Fractional‐Order Uncertain Nonlinear Multiagent Systems

Bai

2018

Complexity

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Due to the excellent approximation ability, the neural networks based control method is used to achieve adaptive consensus of the fractional-order uncertain nonlinear multiagent systems with external disturbance. The unknown nonlinear term and the external disturbance term in the systems are compensated by using the radial basis function neural networks method, a corresponding fractional-order adaption law is designed to approach the ideal neural network weight matrix of the unknown nonlinear terms, and a control law is designed eventually. According to the designed Lyapunov candidate function and the fractional theory, the systems stability is proved, and the adaptive consensus can be guaranteed by using the designed control law. Finally, two simulations are shown to illustrate the validity of the obtained results.

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Consensus of linear multi‐agent systems subject to communication delays and switching networks

Cited by 23 publications

References 31 publications

Leader‐following consensus of multiple uncertain Euler‐Lagrange systems

Leader‐following consensus of multiple uncertain Euler‐Lagrange systems

Consensus analysis of multi-agent systems with general linear dynamics and switching topologies by non-monotonically decreasing Lyapunov function

Neural Networks Based Adaptive Consensus for a Class of Fractional‐Order Uncertain Nonlinear Multiagent Systems

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