Adaptive consensus of multi-agents in networks with jointly connected topologies

Yu, Hui; Xia, Xiaohua

doi:10.1016/j.automatica.2012.05.068

Cited by 243 publications

(170 citation statements)

References 25 publications

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“…It is worthwhile to mention here that the leader-following consensus problem of multi-agent systems with heterogeneous unknown nonlinear dynamics was also investigated using adaptive control in [38,39] and fuzzy disturbance observer in [40], but they only consider agents with first-order dynamics. In this paper, the results in [38][39][40] were largely extended to the multi-agent systems with more general agent dynamics described by (1)- (2). Therefore, the results of this paper are expected to be a necessary complement to the consensus development of general nonlinear multi-agent systems.…”

Section: Stability Analysismentioning

confidence: 99%

Adaptive Leader-Following Consensus of Multi-Agent Systems with Unknown Nonlinear Dynamics

Wang

Chen

2014

Entropy

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This paper deals with the leader-following consensus of multi-agent systems with matched nonlinear dynamics. Compared with previous works, the major difficulty here is caused by the simultaneous existence of nonidentical agent dynamics and unknown system parameters, which are more practical in real-world applications. To tackle this difficulty, a distributed adaptive control law for each follower is proposed based on algebraic graph theory and algebraic Riccati equation. By a Lyapunov function method, we show that the designed control law guarantees that each follower asymptotically converges to the leader under connected communication graphs. A simulation example demonstrates the effectiveness of the proposed scheme.

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Section: Stability Analysismentioning

confidence: 99%

Adaptive Leader-Following Consensus of Multi-Agent Systems with Unknown Nonlinear Dynamics

Wang

Chen

2014

Entropy

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“…The success of the proposed control in (Li et al, 2013) relies on the symmetry in the network connection of an undirected graph. Many adaptive schemes for consensus control requires that the connection graph is undirected to achieve decentralised adaptive laws (Su, Chen, Wang and Lin, 2011;Yu and Xia, 2012;Su and Huang, 2013). For a directed connection graph, the adaptive schemes in (Das and Lewis, 2010;Zhang and Lewis, 2012) achieved consensus control at a price of sacrificing the asymptotic convergence.…”

Section: Introductionmentioning

confidence: 99%

Distributed adaptive consensus control of nonlinear output-feedback systems on directed graphs

Ding

2016

Automatica

119

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This paper deals with consensus control in leader-follower format of a class of network-connected uncertain nonlinear systems by output feedback. Each subsystem is in the nonlinear output feedback form with unknown parameters, and the connection graph among the subsystems is directed. Distributed adaptive control inputs are designed to achieve the consensus control in the sense that the subsystem states asymptotically follow the subsystem at node 0 with no input, which is also known as the leader. The proposed adaptive control only uses relative output measurements and the local information of the connection to each subsystem, and hence the proposed adaptive control is fully distributed. The proposed scheme is different from the consensus output regulation schemes literature, and the leader plays a similar role as a reference model in the classic model reference adaptive control.

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“…There are more diverse results relating to consensus control in recent years, including adaptive control, output regulation and synchronisation, and semiglobal stability (see [5], [6], [7], for example). For adaptive control of network connected systems when the connection graph is undirected, the symmetry of the Laplacian matrix is exploited in the design of adaptive laws [8], [9], [10]. Adaptive consensus control with directed connection graphs is more challenging.…”

Section: Introductionmentioning

confidence: 99%

Distributed Adaptive Consensus Output Regulation of Network-Connected Heterogeneous Unknown Linear Systems on Directed Graphs

Ding

2017

IEEE Trans. Automat. Contr.

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Abstract-This technical note deals with output regulation of network connected linear systems under directed connection graphs. The subsystem dynamics are unknown and heterogeneous. The desired output signal, generated by a linear exosystem, is only available to some subsystems, and the others will estimate the exosystem state through the network connections for obtaining regulation errors. The exosystem is parametrised in a specific form such that it has a skew-symmetric system matrix, whose property is further explored in the estimation of exosystem state, and in the estimation of the desired feed-forward control inputs for output regulation. The unknown subsystem parameters are dealt with by the adaptive laws, driven by the estimated regulation errors. The proposed adaptive control strategy is fully distributed, in the sense that the control design only uses the information in the connected neighbourhood, without reference to the eigenstructure of the associated Laplacian matrix, as long as the connection graph is strongly connected.

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Adaptive consensus of multi-agents in networks with jointly connected topologies

Cited by 243 publications

References 25 publications

Adaptive Leader-Following Consensus of Multi-Agent Systems with Unknown Nonlinear Dynamics

Adaptive Leader-Following Consensus of Multi-Agent Systems with Unknown Nonlinear Dynamics

Distributed adaptive consensus control of nonlinear output-feedback systems on directed graphs

Distributed Adaptive Consensus Output Regulation of Network-Connected Heterogeneous Unknown Linear Systems on Directed Graphs

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