Journal
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
Volume 60, Issue 12, Pages 3310-3315Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TAC.2015.2416927
Keywords
Consensus; distributed optimization; Lyapunov function; second-order multi-agent network
Funding
- National Natural Science Foundation of China [61473333]
- Program for New Century Excellent Talents in University of China [NCET-12-0114]
- Research Grants Council of the Hong Kong Special Administrative Region, China [CUHK416812E]
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This technical note presents a second-order multi-agent network for distributed optimization with a sum of convex objective functions subject to bound constraints. In the multi-agent network, the agents connect each others locally as an undirected graph and know only their own objectives and constraints. The multi-agent network is proved to be able to reach consensus to the optimal solution under mild assumptions. Moreover, the consensus of the multi-agent network is converted to the convergence of a dynamical system, which is proved using the Lyapunov method. Compared with existing multi-agent networks for optimization, the second-order multi-agent network herein is capable of solving more general constrained distributed optimization problems. Simulation results on two numerical examples are presented to substantiate the performance and characteristics of the multi-agent network.
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