Distributed Continuous-time Optimization with Scalable Adaptive Event-based Mechanisms

Zizhen Wu; Zhenhong Li; Zhengtao Ding; Zhongkui Li

doi:10.1109/TSMC.2018.2867175

Distributed Continuous-time Optimization with Scalable Adaptive Event-based Mechanisms

Zizhen Wu, Zhenhong Li, Zhengtao Ding, Zhongkui Li

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Abstract

This paper investigates the distributed continuoustime optimization problem, which consists of a group of agents with variant local cost functions. An adaptive consensus-based algorithm with event triggering communications is introduced,
which can drive the participating agents to minimize the global cost function and exclude the Zeno behavior. Compared to the existing results, the proposed event-based algorithm is independent of the parameters of the cost functions, using only the relative information of neighboring agents, and hence is fully distributed.
Furthermore, the constraints of the convexity of the cost functions are relaxed.

Original language	English
Journal	IEEE Transactions on Systems, Man and Cybernetics: Systems
Early online date	10 Sept 2018
DOIs	https://doi.org/10.1109/TSMC.2018.2867175
Publication status	Published - 2018

Keywords

Distributed optimization
event-triggered control
cooperative control
adaptive control

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10.1109/TSMC.2018.2867175

2018TSMCAccepted author manuscript, 608 KB

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title = "Distributed Continuous-time Optimization with Scalable Adaptive Event-based Mechanisms",

abstract = "This paper investigates the distributed continuoustime optimization problem, which consists of a group of agents with variant local cost functions. An adaptive consensus-based algorithm with event triggering communications is introduced,which can drive the participating agents to minimize the global cost function and exclude the Zeno behavior. Compared to the existing results, the proposed event-based algorithm is independent of the parameters of the cost functions, using only the relative information of neighboring agents, and hence is fully distributed.Furthermore, the constraints of the convexity of the cost functions are relaxed.",

keywords = "Distributed optimization, event-triggered control, cooperative control, adaptive control",

author = "Zizhen Wu and Zhenhong Li and Zhengtao Ding and Zhongkui Li",

year = "2018",

doi = "10.1109/TSMC.2018.2867175",

language = "English",

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AU - Wu, Zizhen

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AU - Ding, Zhengtao

AU - Li, Zhongkui

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Y1 - 2018

N2 - This paper investigates the distributed continuoustime optimization problem, which consists of a group of agents with variant local cost functions. An adaptive consensus-based algorithm with event triggering communications is introduced,which can drive the participating agents to minimize the global cost function and exclude the Zeno behavior. Compared to the existing results, the proposed event-based algorithm is independent of the parameters of the cost functions, using only the relative information of neighboring agents, and hence is fully distributed.Furthermore, the constraints of the convexity of the cost functions are relaxed.

AB - This paper investigates the distributed continuoustime optimization problem, which consists of a group of agents with variant local cost functions. An adaptive consensus-based algorithm with event triggering communications is introduced,which can drive the participating agents to minimize the global cost function and exclude the Zeno behavior. Compared to the existing results, the proposed event-based algorithm is independent of the parameters of the cost functions, using only the relative information of neighboring agents, and hence is fully distributed.Furthermore, the constraints of the convexity of the cost functions are relaxed.

KW - Distributed optimization

KW - event-triggered control

KW - cooperative control

KW - adaptive control

U2 - 10.1109/TSMC.2018.2867175

DO - 10.1109/TSMC.2018.2867175

M3 - Article

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JO - IEEE Transactions on Systems, Man and Cybernetics: Systems

JF - IEEE Transactions on Systems, Man and Cybernetics: Systems

ER -

Distributed Continuous-time Optimization with Scalable Adaptive Event-based Mechanisms

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Keywords

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