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    A Stabilizing Control Algorithm for Asynchronous Parallel Quadratic Programing via Dual Decomposition

    Source: ASME Letters in Dynamic Systems and Control:;2021:;volume( 001 ):;issue: 001::page 011002-1
    Author:
    Lee, Kooktae
    DOI: 10.1115/1.4046365
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper proposes a control algorithm for stable implementation of asynchronous parallel quadratic programing (PQP) through a dual decomposition technique. In general, distributed and parallel optimization requires synchronization of data at each iteration step due to the interdependency of data. The synchronization latency may incur a large amount of waiting time caused by an idle process during computation. We aim to mitigate this synchronization penalty in PQP problems by implementing asynchronous updates of the dual variable. The price to pay for adopting asynchronous computing algorithms is the unpredictability of the solution, resulting in a tradeoff between speedup and accuracy. In the worst case, the state of interest may become unstable owing to the stochastic behavior of asynchrony. The stability condition of asynchronous PQP problems is investigated by employing the switched system framework. A formal algorithm is provided to ensure the asymptotic stability of dual variables. Furthermore, it is shown that the implementation of the proposed algorithm guarantees the uniqueness of optimal solutions, irrespective of asynchronous behavior. To verify the validity of the proposed methods, simulation results are presented.
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      A Stabilizing Control Algorithm for Asynchronous Parallel Quadratic Programing via Dual Decomposition

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    contributor authorLee, Kooktae
    date accessioned2022-02-04T23:00:34Z
    date available2022-02-04T23:00:34Z
    date copyright1/1/2021 12:00:00 AM
    date issued2021
    identifier issn2689-6117
    identifier otheraldsc_1_1_011002.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4275898
    description abstractThis paper proposes a control algorithm for stable implementation of asynchronous parallel quadratic programing (PQP) through a dual decomposition technique. In general, distributed and parallel optimization requires synchronization of data at each iteration step due to the interdependency of data. The synchronization latency may incur a large amount of waiting time caused by an idle process during computation. We aim to mitigate this synchronization penalty in PQP problems by implementing asynchronous updates of the dual variable. The price to pay for adopting asynchronous computing algorithms is the unpredictability of the solution, resulting in a tradeoff between speedup and accuracy. In the worst case, the state of interest may become unstable owing to the stochastic behavior of asynchrony. The stability condition of asynchronous PQP problems is investigated by employing the switched system framework. A formal algorithm is provided to ensure the asymptotic stability of dual variables. Furthermore, it is shown that the implementation of the proposed algorithm guarantees the uniqueness of optimal solutions, irrespective of asynchronous behavior. To verify the validity of the proposed methods, simulation results are presented.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleA Stabilizing Control Algorithm for Asynchronous Parallel Quadratic Programing via Dual Decomposition
    typeJournal Paper
    journal volume1
    journal issue1
    journal titleASME Letters in Dynamic Systems and Control
    identifier doi10.1115/1.4046365
    journal fristpage011002-1
    journal lastpage011002-6
    page6
    treeASME Letters in Dynamic Systems and Control:;2021:;volume( 001 ):;issue: 001
    contenttypeFulltext
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