Distributed Optimization for Continuous Time Multiple Agents Systems With Unknown Parameters

This paper addresses a distributed convex optimization problem with objective functions for arbitrary order continuous time multiply agents systems with unknown parameters. In this paper, the control objective is not only to drive the multiply agents to reach a consensus, but also to cooperatively m...

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Bibliographic Details
Published in2019 Chinese Control Conference (CCC) pp. 2430 - 2435
Main Authors Hu, Zilun, Yang, Jianying
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 01.07.2019
Subjects
Adaptive control
Adaptive systems
Convex functions
Distributed optimization
Heuristic algorithms
Linear programming
Multiply agents
Optimization
Task analysis
Trajectory
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Summary:This paper addresses a distributed convex optimization problem with objective functions for arbitrary order continuous time multiply agents systems with unknown parameters. In this paper, the control objective is not only to drive the multiply agents to reach a consensus, but also to cooperatively minimize the team objective function with consensus requirement. Different from the traditional optimization problems, in this paper, the proposed method is distributed, which means that the agent can only acquire the information of its neighbors' objective function through the network connection. Theoretical studies indicate that the proposed algorithms can minimize the team objective function and all agents will reach a consensus. Some simulation examples are presented to show the validity of the theoretical results.
ISSN:2161-2927
DOI:10.23919/ChiCC.2019.8866418