Distributed Quantized Optimization Design of Continuous-Time Multiagent Systems Over Switching Graphs

This article focuses on the distributed quantized optimization problem of continuous-time multiagent systems (MASs) over switching graphs. By proposing a dynamic encoding-decoding scheme, a distributed protocol via sampled and quantized data is developed, which can obtain an exact optimal solution,...

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Bibliographic Details
Published in:IEEE transactions on systems, man, and cybernetics. Systems Vol. 51; no. 11; pp. 7152 - 7163
Main Authors: Chen, Ziqin, Ji, Haibo
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Cost function
Design optimization
Distributed optimization
Graphs
Multi-agent systems
Multiagent systems
multiagent systems (MASs)
Optimization
Protocols
quantization
Quantization (signal)
Switches
Switching
switching graphs
ISSN:2168-2216, 2168-2232
Online Access:Get full text
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Summary:This article focuses on the distributed quantized optimization problem of continuous-time multiagent systems (MASs) over switching graphs. By proposing a dynamic encoding-decoding scheme, a distributed protocol via sampled and quantized data is developed, which can obtain an exact optimal solution, rather than an approximate optimal solution. Compared with existing works on quantized distributed optimization of MASs, the protocol presented in this article does not require the global information on the communication graph or the initial state. Besides, in this article, the gradients of the cost functions are not required to be bounded functions. A simulation example is finally presented to illustrate the effectiveness of the proposed distributed protocol.
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ISSN:2168-2216
2168-2232
DOI:10.1109/TSMC.2020.2966636