Distributed continuous‐time constrained convex optimization with general time‐varying cost functions

The distributed time‐varying constrained convex optimization problem over a connected undirected network topology is studied in this article. The proposed distributed optimization algorithm is composed of a projection map term, a consensus term, and a gradient term, and is feasible for any initial c...

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Veröffentlicht in:International journal of robust and nonlinear control Jg. 31; H. 6; S. 2222 - 2236
Hauptverfasser: Huang, Bomin, Zou, Yao, Meng, Ziyang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.04.2021
Schlagworte:
Algorithms
Computational geometry
constraint set
Constraints
Convergence
Convex analysis
Convexity
Cost function
distributed convex optimization
Network topologies
Optimization algorithms
time‐varying cost function
Trajectory optimization
ISSN:1049-8923, 1099-1239
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Zusammenfassung:The distributed time‐varying constrained convex optimization problem over a connected undirected network topology is studied in this article. The proposed distributed optimization algorithm is composed of a projection map term, a consensus term, and a gradient term, and is feasible for any initial condition. We first show that the states of the optimization algorithm uniformly converge to a neighborhood of the constraint set while an approximate global consensus is achieved. Then the states are proven to uniformly converge to a neighborhood of the time‐varying optimal trajectory. The theoretical results are validated by some simulations.
Bibliographie:Funding information
National Natural Science Foundation of China, 61873140, U19B2029, 61833009, 62073028; Beijing Natural Science Foundation, JQ20013; Graduate Education and Teaching Reform Project ot Tsinghua University, 202007J007
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ISSN:1049-8923
1099-1239
DOI:10.1002/rnc.5383