Distributed output regulation for multi-agent systems with norm-bounded uncertainties

Lu, Yu; Wang, Jinzhi

doi:10.1080/00207721.2013.769647

Cited by 16 publications

(9 citation statements)

References 45 publications

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“…Both algorithms  1 and  2 are simulated. For each agent, we employ five hidden nodes in the neural networks, which means that ( We first apply the iterative learning protocol  1 (10) with adaptive laws (11) and (12) to the MAS. The learning parameters are set to be j = 10, j = 10, and g 0 = 1.…”

Section: Illustrative Simulationsmentioning

confidence: 99%

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

Shen

Zhang

2019

Intl J Robust & Nonlinear

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Summary This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.

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Section: Illustrative Simulationsmentioning

confidence: 99%

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

Shen

Zhang

2019

Intl J Robust & Nonlinear

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“…The conventional output regulation for both linear and nonlinear systems has been studied for many decades [16], [17]. Output regulation for multi-agent systems has been studied by a lot of researchers [18]- [24]. Output regulation problem of state-coupled linear certain and uncertain multiagent systems with globally reachable topologies was investigated by [18], in which exosystem is same for all the nodes but only partial nodes have the state information channel with it.…”

Section: Introductionmentioning

confidence: 99%

“…Ref [19] solved the regulation problem in the case that only partial agents could be measured by itself and its neighbors, and a full order Luenberger observer is given for the unmeasurable part. Heterogeneous agents were considered by [23], [24], and the compensator method was used in [23]. Small gain method was first used in solving output regulation problem in [24].…”

Section: Introductionmentioning

confidence: 99%

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Distributed control for second-order leader-following multi-agent systems with heterogeneous leader

Liang

Wang

et al. 2014

2014 International Joint Conference on Neural Networks (IJCNN)

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In this paper, distributed control for second-order leader-following multi-agent systems has been solved. All the outputs of the agents reach a common trajectory. The dynamic of the leader agent is different with the follower agents. If the digraph contains a spanning tree, then the problem is solved using an appropriate control law. A compensator is designed to making the closed-loop system matrix stable. Simulation results are further presented to show the effectiveness and performance of our work.

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“…In addition, the containment control problem for heterogeneous linear multi-agent systems was studied based on output regulation approach (Haghshenas, Badamchizadeh, & Baradarannia, 2015). Excellent results about this type of problem were also given in Hong, Wang, and Jiang (2013) ;Li, Feng, Wang, Luo, and Guan (2014); Yu and Wang (2014).…”

Section: Introductionmentioning

confidence: 99%

Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach

Liao

Deng

et al. 2017

International Journal of Systems Science

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This paper investigates the cooperative global optimal preview tracking problem of linear multi-agent systems under the assumption that the output of a leader is a previewable periodic signal and the topology graph contains a directed spanning tree. First, a type of distributed internal model is introduced, and the cooperative preview tracking problem is converted to a global optimal regulation problem of an augmented system. Second, an optimal controller, which can guarantee the asymptotic stability of the augmented system, is obtained by means of the standard linear quadratic optimal preview control theory. Third, on the basis of proving the existence conditions of the controller, sufficient conditions are given for the original problem to be solvable, meanwhile a cooperative global optimal controller with error integral and preview compensation is derived. Finally, the validity of theoretical results is demonstrated by a numerical simulation.

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Distributed output regulation for multi-agent systems with norm-bounded uncertainties

Cited by 16 publications

References 45 publications

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

Distributed control for second-order leader-following multi-agent systems with heterogeneous leader

Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach

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