A continuous-time algorithm based on multi-agent system for distributed least absolute deviation subject to hybrid constraints

In this paper, a continuous-time distributed optimization algorithm based on multi-agent system is proposed for solving the distributed least absolute deviation problems subject to hybrid constraints. In the multi-agent network, each of the L 1 -norm functions is realized using the projection operat...

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Vydané v:IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society s. 7381 - 7386
Hlavní autori: Qingshan Liu, Kaixuan Li
Médium: Konferenčný príspevok..
Jazyk:English
Japanese
Vydavateľské údaje: IEEE 01.10.2017
Predmet:
consensus
Couplings
Distributed algorithms
distributed optimization
Heuristic algorithms
Least absolute deviation
Linear programming
Mathematical model
multi-agent network
Multi-agent systems
Optimization
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Shrnutí:In this paper, a continuous-time distributed optimization algorithm based on multi-agent system is proposed for solving the distributed least absolute deviation problems subject to hybrid constraints. In the multi-agent network, each of the L 1 -norm functions is realized using the projection operator. Meanwhile, each agent must be subject to the local hybrid constraints. Then all the agents constitute a network with connected graph to cooperate to seek the optimal solutions with consensus. The performance of the proposed distributed algorithm is illustrated using a numerical example with simulations.
DOI:10.1109/IECON.2017.8217293