Finite-time formation-containment tracking for second-order multi-agent systems with a virtual leader of fully unknown input

Liao, Ruiwen; Han, Liang; Dong, Xiwang; Li, Qingdong; Zhang, Ren

doi:10.1016/j.neucom.2020.07.067

Cited by 53 publications

(20 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this case, since the leader is virtual, there is no formation problem due to leader failure. Liao R. et al [3] designed a multi-agent system as a formation composed of a virtual leader with a completely unknown input and several real leaders and followers. Then, distributed finite-time observers were designed for each real leader and follower to obtain state estimates of the adjacent agents.…”

Section: Of 27mentioning

confidence: 99%

Formation Control of a Multi-Autonomous Underwater Vehicle Event-Triggered Mechanism Based on the Hungarian Algorithm

Zhang

2021

Machines

View full text Add to dashboard Cite

Among the key technologies of Autonomous Underwater Vehicle (AUV) leader–follower formations control, formation reconfiguration technology is one of the main technologies to ensure that multiple AUVs successfully complete their tasks in a complex operating environment. The biggest drawback of the leader–follower formations technology is the failure of the leader and the excessive communication pressure of the leader. Aiming at the problem of leader failure in multi- AUV leader–follower formations, the Hungarian algorithm is used to reconstruct the failed formation with a minimum cost, and the improvement of the Hungarian algorithm can solve the problem of a non-standard assignment. In order to solve the problem of an increased leader communication task after formation reconfiguration, the application of an event-triggered mechanism (ETM) can reduce unnecessary and useless communication, while the efficiency of the ETM can be improved through increasing the event-triggered conditions of the sampling error threshold. The simulation results of multi-AUV formation control show that the Hungarian algorithm proposed in this paper can deal with the leader failure in the multi-AUV leader–follower formation, and the ETM designed in this paper can reduce about 90% of the communication traffic of the formation which also proves the highly efficient performance of the improved ETM in the paper.

show abstract

Section: Of 27mentioning

confidence: 99%

Formation Control of a Multi-Autonomous Underwater Vehicle Event-Triggered Mechanism Based on the Hungarian Algorithm

Zhang

2021

Machines

View full text Add to dashboard Cite

show abstract

“…In recent years, much attention has been received for multi-agent systems because of its wide application, such as military [1], energy management [2], sensor network [3], transport [4], etc. In practice, agents often need to have a common goal, reach the same place or work in the same state, etc.…”

Section: Introductionmentioning

confidence: 99%

Consensus of Heterogeneous Multi-Agent Systems Under Directed Topology

Geng

Miao

et al. 2022

IEEE Access

View full text Add to dashboard Cite

In this paper, the consensus problem of heterogeneous multi-agent systems under directed topology is investigated. Specifically, this system is composed of three classes of agents respectively described by first-order, second-order and third-order integrator dynamics. By the aid of linear filter, graph theory and matrix theory, the consensus problem is realized based on the two proposed consensus protocols. Moreover, group consensus can also be solved by adjusting parameters. Finally, some examples were presented to illustrate the theoretical results. Our study is expected to establish a more realistic model and provide a method to solve the consensus problem of heterogeneous multi-agent systems in more complex situations.INDEX TERMS Consensus, directed topology, multi-agent systems, heterogeneous, linear filter.

show abstract

“…Typically, the objective is to establish a coordinative protocol for networked systems such that the prescribed formation defined by relative states among agents is achieved. To realize the formation control, several methods have been developed in the existing literature, including leader‐following strategies, 18,19 behavior‐based methods, 20,21 and virtual structure approaches 22,23 …”

Section: Introductionmentioning

confidence: 99%

“…To realize the formation control, several methods have been developed in the existing literature, including leader-following strategies, 18,19 behavior-based methods, 20,21 and virtual structure approaches. 22,23 In the execution of cooperative transportation tasks by multirobot systems, 24,25 it is expected that all robots keep the expected relative positions in the overall motion process. Driven by these applications, the iterative learning approach is used to the formation control for multiple agents, [26][27][28][29][30][31][32] which can ensure the formation keeping within the entire movement by using the control experiences from previous trials.…”

Section: Introductionmentioning

confidence: 99%

An iterative learning approach to formation control of discrete‐time multi‐agent systems With varying trial lengths

Liu

Fan²,

et al. 2022

Intl J Robust & Nonlinear

View full text Add to dashboard Cite

In this article, an iterative learning approach is proposed for the formation control of discrete-time multi-agent systems, where the trial length of each learning iteration is randomly varying. In particular, a modified state error related to the prescribed formation is defined by taking into account the nonuniform actual trial length that could be different from the desired one. Then, a P-type iterative learning protocol is established for switching networks of agents subject to nonuniform trial lengths, and the convergence analyses are given for the fixed and the iteration-varying initial conditions respectively. It shows that through iterative learning, the given formation will be maintained among multiple agents in the entire time interval of one trial. In the end, simulations are done to demonstrate the correctness of the obtained theoretical results.

show abstract

Finite-time formation-containment tracking for second-order multi-agent systems with a virtual leader of fully unknown input

Cited by 53 publications

References 33 publications

Formation Control of a Multi-Autonomous Underwater Vehicle Event-Triggered Mechanism Based on the Hungarian Algorithm

Formation Control of a Multi-Autonomous Underwater Vehicle Event-Triggered Mechanism Based on the Hungarian Algorithm

Consensus of Heterogeneous Multi-Agent Systems Under Directed Topology

An iterative learning approach to formation control of discrete‐time multi‐agent systems With varying trial lengths

Contact Info

Product

Resources

About