Event-based broadcasting for multi-agent average consensus
A novel control strategy for multi-agent coordination with event-based broadcasting is presented. In particular, each agent decides itself when to transmit its current state to its neighbors and the local control laws are based on these sampled state measurements. Three scenarios are analyzed: Netwo...
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| Vydáno v: | Automatica (Oxford) Ročník 49; číslo 1; s. 245 - 252 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Kidlington
Elsevier Ltd
01.01.2013
Elsevier |
| Témata: | |
| ISSN: | 0005-1098, 1873-2836, 1873-2836 |
| On-line přístup: | Získat plný text |
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| Abstract | A novel control strategy for multi-agent coordination with event-based broadcasting is presented. In particular, each agent decides itself when to transmit its current state to its neighbors and the local control laws are based on these sampled state measurements. Three scenarios are analyzed: Networks of single-integrator agents with and without communication delays, and networks of double-integrator agents. The novel event-based scheduling strategy bounds each agent’s measurement error by a time-dependent threshold. For each scenario it is shown that the proposed control strategy guarantees either asymptotic convergence to average consensus or convergence to a ball centered at the average consensus. Moreover, it is shown that the inter-event intervals are lower-bounded by a positive constant. Numerical simulations show the effectiveness of the novel event-based control strategy and how it compares to time-scheduled control. |
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| AbstractList | A novel control strategy for multi-agent coordination with event-based broadcasting is presented. In particular, each agent decides itself when to transmit its current state to its neighbors and the local control laws are based on these sampled state measurements. Three scenarios are analyzed: Networks of singleintegrator agents with and without communication delays, and networks of double-integrator agents. The novel event-based scheduling strategy bounds each agent’s measurement error by a time-dependent threshold. For each scenario it is shown that the proposed control strategy guarantees either asymptotic convergence to average consensus or convergence to a ball centered at the average consensus. Moreover, it is shown that the inter-event intervals are lower-bounded by a positive constant. Numerical simulations show the effectiveness of the novel event-based control strategy and how it compares to time-scheduled control. A novel control strategy for multi-agent coordination with event-based broadcasting is presented. In particular, each agent decides itself when to transmit its current state to its neighbors and the local control laws are based on these sampled state measurements. Three scenarios are analyzed: Networks of single-integrator agents with and without communication delays, and networks of double-integrator agents. The novel event-based scheduling strategy bounds each agent’s measurement error by a time-dependent threshold. For each scenario it is shown that the proposed control strategy guarantees either asymptotic convergence to average consensus or convergence to a ball centered at the average consensus. Moreover, it is shown that the inter-event intervals are lower-bounded by a positive constant. Numerical simulations show the effectiveness of the novel event-based control strategy and how it compares to time-scheduled control. A novel control strategy for multi-agent coordination with event-based broadcasting is presented. In particular, each agent decides itself when to transmit its current state to its neighbors and the local control laws are based on these sampled state measurements. Three scenarios are analyzed: Networks of single-integrator agents with and without communication delays, and networks of double-integrator agents. The novel event-based scheduling strategy bounds each agentas measurement error by a time-dependent threshold. For each scenario it is shown that the proposed control strategy guarantees either asymptotic convergence to average consensus or convergence to a ball centered at the average consensus. Moreover, it is shown that the inter-event intervals are lower-bounded by a positive constant. Numerical simulations show the effectiveness of the novel event-based control strategy and how it compares to time-scheduled control. |
| Author | Seyboth, Georg S. Dimarogonas, Dimos V. Johansson, Karl H. |
| Author_xml | – sequence: 1 givenname: Georg S. surname: Seyboth fullname: Seyboth, Georg S. email: georg.seyboth@ist.uni-stuttgart.de organization: Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70550 Stuttgart, Germany – sequence: 2 givenname: Dimos V. surname: Dimarogonas fullname: Dimarogonas, Dimos V. email: dimos@ee.kth.se organization: ACCESS Linnaeus Center, School of Electrical Engineering, Royal Institute of Technology (KTH), 100 44 Stockholm, Sweden – sequence: 3 givenname: Karl H. surname: Johansson fullname: Johansson, Karl H. email: kallej@ee.kth.se organization: ACCESS Linnaeus Center, School of Electrical Engineering, Royal Institute of Technology (KTH), 100 44 Stockholm, Sweden |
| BackLink | http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=26786195$$DView record in Pascal Francis https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-111424$$DView record from Swedish Publication Index (Kungliga Tekniska Högskolan) |
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| CODEN | ATCAA9 |
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| SubjectTerms | Applied sciences Artificial intelligence Asymptotic properties Broadcasting Computer science; control theory; systems Computer systems and distributed systems. User interface Consensus Control system synthesis Control theory. Systems Convergence Cooperative control Delay Error analysis Event-based control Exact sciences and technology Multi-agent systems Multiagent systems Networked control systems Networks Robotics Software Strategy |
| Title | Event-based broadcasting for multi-agent average consensus |
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