Multi-agent formation control in switching networks using backstepping design

Wang, Qin; Hua, Qingguang; Yi, Yang; Zhang, Tianping

doi:10.1007/s12555-016-0166-8

Cited by 14 publications

(7 citation statements)

References 16 publications

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“…), and the edges in E c are assigned to n À 2 distinct vertices belong to V s in a scalable way via communication. We choose the initialized edge as (1,15; the initialized edge is not unique), and the output of the algorithm is as follows 15, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, f 13, 14, 16, 17, 18, 19, 20g (1,15), (1,2), (1,3), (1,4), (2,5), (2,6), (2,7), f…”

Section: Simulationsmentioning

confidence: 99%

“…(3, 8), (3,9), (1,10), (2,11), (8,12), (4, 13), (7,14), (1,16), (11,17), (9,18), (3,19), (8,20)g 3, 4, 5, 6, 7, 15, 8, 9, 10, 11, 12, f 13, 14, 16, 17, 18, 19, 20g E c = f(3, 2), (4, 3), (5,4), (6,4), (7,6), (7,15), (8,5), (9,8), (10,3), (11,3), (12,11), (13,11), (14,13), (16,13), (17,12), (18,11), (19,12), …”

Section: Simulationsmentioning

confidence: 99%

“…A formation system can be described from three main aspects: 1 the geometrical shape, the communication topology, and the control strategy. There have been three approaches describing multi-agent formation, that is, displacementbased formation control, [2][3][4][5][6] distance-based formation control, [7][8][9] and bearing-only formation control. [10][11][12][13] Among the three approaches, distance-based formation control is regarded as a more ideal distributed approach, since the collision between the neighboring agents can be avoided.…”

Section: Introductionmentioning

confidence: 99%

“…, and the edges in E c are assigned to n À 2 distinct vertices belong to V s in a scalable way via communication. We choose the initialized edge as (1,15; the initialized edge is not unique), and the output of the algorithm is as follows (3,9), (1, 10), (2, 11), (8,12), (4, 13), (7,14), (1,16), (11,17), (9,18), (3,19), (8,20)g 3, 4, 5, 6, 7, 15, 8, 9, 10, 11, 12, f 13, 14, 16, 17, 18, 19, 20g E c = f(3, 2), (4, 3), (5,4), (6,4), (7, 6), (7,15), (8,5), (9,8), (10,3), (11,3), (12,11), (13,11), (14,13), (16,13), (17,12), (18,11), (19,12), (20,…”

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confidence: 99%

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A scalable algorithm for the decomposition of minimally rigid graph

Zhu

Kang

et al. 2020

Measurement and Control

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The rigid graph needs to be decomposed to solve the multi-equilibrium problem of the multi-agent formation control based on navigation function method. In this paper, a theorem and a scalable algorithm based on the Henneberg sequence of graphs are proposed for the decomposition of minimally rigid graph. The theorem demonstrates that if graph G(V, E) is a minimally rigid graph, then it can be decomposed as G = G t [ G c , where G t is a spanning tree of G and G c contains the remaining edges and their vertices. Moreover, the scalable algorithm is given to construct G t = (V t , E t ) and G c = (V c , E c ), and assign the edges in E c to n -2 distinct vertices in a scalable way via communication. Furthermore, a lemma is given to show when the number of vertices is less than eight, any edge can be chosen as the initialized edge, and the scalable algorithm mentioned above is always feasible. Finally, the effectiveness of the scalable algorithm is verified by numerical simulation.

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Section: Simulationsmentioning

confidence: 99%

Section: Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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A scalable algorithm for the decomposition of minimally rigid graph

Zhu

Kang

et al. 2020

Measurement and Control

Self Cite

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“…Each AV shares its states with others by V2V [7]. Such information connections are unreliable because wireless communication is easily degraded by adverse environments [19][20][21]. Moreover, each AV can hardly get the information of all AVs because of the limitation of communication range.…”

Section: Problem Descriptionmentioning

confidence: 99%

Distributed sliding mode control for formation of multiple nonlinear AVs coupled by uncertain topology

Gao

Bao

et al. 2019

SN Appl. Sci.

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To combat the variety uncertainties in topologies, dynamical models and disturbances, this paper presents a distributed sliding mode control strategy for formation control of multiple AVs. In this scheme, all collected information of each AV is used for its control and different perturbations are dealt with separately to reduce the contractions among them. Furthermore, a distributed adaptive algorithm is designed to replace the witching part for smoothness of control. The convergence of sliding surfaces of both two controllers is analysed theoretically. The sliding dynamics is affected by both the feedback and interaction topology. The existing decoupling method to handle the variety topologies can be used to synthesize the sliding dynamics. Finally, this approach has been applied to vehicular platooning and validated by several comparative simulations. The results show that the proposed method can control multiple AVs better than the state feedback strategy.

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Command filtered backstepping‐based containment control for a class of multi‐agent systems with uncertainty

Jiang

Yang

Gao

et al. 2023

Intl J Robust & Nonlinear

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SummaryIn this paper, a novel containment control scheme is designed for multi‐agent systems with unknown parameters and unknown control coefficients. To achieve the containment control goal, containment reference signals are generated using a certain number of dynamic leaders. Then, the followers directly receiving the reference signals can track their generated reference signals, and the rest of the followers track a certain number of estimated signals generated by designed dynamic equations. Under the backstepping framework, uncertainties of a multi‐agent system are compensated for through the adaptive bound estimation method. Additionally, the command filtered technique is adopted to avoid the cumbersome steps of multiple derivative calculations, and to simplify the operations of the control scheme. Finally, the stability of the closed‐loop multi‐agent system is proved based on the Lyapunov theory. The advantage of the proposed scheme is that the containment reference signal and the position between followers can be adjusted arbitrarily by adjusting the relevant parameters. Through simulations, the effectiveness and superiority of the designed controller are verified.

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Multi-agent formation control in switching networks using backstepping design

Cited by 14 publications

References 16 publications

A scalable algorithm for the decomposition of minimally rigid graph

A scalable algorithm for the decomposition of minimally rigid graph

Distributed sliding mode control for formation of multiple nonlinear AVs coupled by uncertain topology

Command filtered backstepping‐based containment control for a class of multi‐agent systems with uncertainty

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