Semi-global containment control of multi-agent systems with intermittent input saturation

Su, Housheng; Gui, Jia; Chen, Michael Z. Q.

doi:10.1016/j.jfranklin.2014.09.006

Cited by 96 publications

(55 citation statements)

References 38 publications

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“…As claimed and demonstrated in [1][2][3][4][5]8,9,13,18,26,29,30], consensus aimed at guiding the states of all agents to achieve a common value is one of the fundamental problems in the coordinated control of multi-agent systems and has attracted considerable attention, ranging from first-order systems [7,23] to second-order systems [10,12,14,20,31] and even high-order ones [21]. For example, the authors in [23] investigated the consensus of first-order multiagent systems subject to input saturation, whereas references [12,20,31] focused on the consensus of second-order multi-agent systems with nonlinear intrinsic dynamics.…”

Section: Introductionmentioning

confidence: 81%

“…Hence, system (18) can reach the second-order consensus only when the following condition is satisfied:…”

Section: Remarkmentioning

confidence: 99%

“…The coordinated control of multi-agent systems, including synchronization [6,11,22,25], flocking [15,22], consensus [7,10,12,14,[20][21][22][23]31] and containment [17][18][19], has become an active research field in recent decades. As claimed and demonstrated in [1][2][3][4][5]8,9,13,18,26,29,30], consensus aimed at guiding the states of all agents to achieve a common value is one of the fundamental problems in the coordinated control of multi-agent systems and has attracted considerable attention, ranging from first-order systems [7,23] to second-order systems [10,12,14,20,31] and even high-order ones [21].…”

Section: Introductionmentioning

confidence: 99%

“…Intermittent control means that the controllers work and rest alternately. To make the theoretical analysis more convenient, in much of the existing literature relating to intermittent control (see [1,2,5,8,9,13,18,26,29,30] and some references therein), the control time was periodic, namely the periodically intermittent control, where each period was divided into "work time" and "rest time." In [5] and [8], the authors investigated the synchronization of chaotic systems and the stabilization of nonlinear systems, respectively, by introducing the periodically intermittent control method.…”

Section: Introductionmentioning

confidence: 99%

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Second-Order Consensus of Multi-agent Systems via Periodically Intermittent Pinning Control

Wang

Liu

2015

Circuits Syst Signal Process

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In this paper, we investigate the leader-following consensus of second-order multi-agent systems with nonlinear dynamics and time delay by employing periodically intermittent pinning control. All member agents and the virtual leader share the same nonlinear dynamics relating to the velocity and delayed velocity information. Based on Lyapunov stability theory, we obtain a novel criterion that is independent of the time delay and control width to guarantee the second-order consensus of multiagent systems with time delay and periodically intermittent controllers. Numerical simulations are presented to illustrate the theoretical results.

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Section: Introductionmentioning

confidence: 81%

“…Hence, system (18) can reach the second-order consensus only when the following condition is satisfied:…”

Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Second-Order Consensus of Multi-agent Systems via Periodically Intermittent Pinning Control

Wang

Liu

2015

Circuits Syst Signal Process

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“…Therefore, the consensus control problem of multi-agent systems with saturation constraints is not only theoretically challenging but also practical. However, there are only a few works devoted to this issue (Meng et al, 2013;Su et al, 2013Su et al, , 2014aSu et al, , 2014bWang et al, 2014aWang et al, , 2014bYang et al, 2014). In particular, Meng et al (2013) studied the global consensus tracking problem for neutrally stable linear systems subject to actuator saturation, and these results were extended to the discrete-time counterpart in Yang et al (2014).…”

Section: Introductionmentioning

confidence: 99%

Adaptive consensus tracking for linear multi-agent systems with input saturation

Chu

Zhang

2016

Transactions of the Institute of Measurement and Control

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This paper addresses the consensus protocol design problem for linear multi-agent systems with input saturation. Existing consensus protocols usually contain certain global information, such as network size or the spectrum of the Laplacian matrix, and this global knowledge is often unavailable to all agents. In this paper, based on only the agent dynamics and the relative states of neighbouring agents, a novel adaptive consensus protocol is designed by assigning a time-varying coupling weight to each node. This protocol has two advantages: it is independent of any global information, and hence is fully distributed; and it is implemented by actuators with input saturation constraints. By combining the low-gain feedback method and appropriate Lyapunov techniques, it is shown that our protocol can achieve the semi-global consensus tracking in a fully distributed fashion, under the mild assumptions on agent dynamics and the topology graph. The results are illustrated by numerical simulations

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An Overview of Cooperative and Consensus Control of Multiagent Systems

Davoodi

Gallehdari

Saboori

et al. 2016

Wiley Encyclopedia of Electrical and Electronics Engineering

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There has been a growing interest toward the development of networked unmanned autonomous systems that can operate without an extensive involvement of humans. The motivation for this focus can be traced to the emergence of applications where direct human intervention is not possible due to the environmental hazards, complexity of the tasks, or other restrictions. These networks can consist of a large number of dynamical systems (agents), such as unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), and unmanned underwater vehicles (UUVs). These systems commonly include a number of sensors, actuators, and decisionmakers. Therefore, the network of these systems is a network of a large number of sensors and actuators or, as is known in the literature, a system of systems (SoS). In this work, we provide a brief overview of controlling these networks, their applications, and the solutions that are proposed for these problems in the literature. Specifically, this article overviews recent results and progress made on multiagent consensus by focusing on cooperative control and consensus (formation) control in the presence of communication, control implementation, and saturation constraints. In addition, we review the active areas of event‐triggered consensus control, network security and attacks on the agents, and networks and resilient consensus control strategies that are proposed to handle these challenges.

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Semi-global containment control of multi-agent systems with intermittent input saturation

Cited by 96 publications

References 38 publications

Second-Order Consensus of Multi-agent Systems via Periodically Intermittent Pinning Control

Second-Order Consensus of Multi-agent Systems via Periodically Intermittent Pinning Control

Adaptive consensus tracking for linear multi-agent systems with input saturation

An Overview of Cooperative and Consensus Control of Multiagent Systems

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