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Volume 8 Issue 7
Jul.  2021

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2021  >  8(7): 1336-1344
T. Bai, S. Y. Li, and Y. Y. Zou, "Distributed MPC for Reconfigurable Architecture Systems via Alternating Direction Method of Multipliers," IEEE/CAA J. Autom. Sinica, vol. 8, no. 7, pp. 1336-1344, Jul. 2021. doi: 10.1109/JAS.2020.1003195
Citation: T. Bai, S. Y. Li, and Y. Y. Zou, "Distributed MPC for Reconfigurable Architecture Systems via Alternating Direction Method of Multipliers," IEEE/CAA J. Autom. Sinica, vol. 8, no. 7, pp. 1336-1344, Jul. 2021. doi: 10.1109/JAS.2020.1003195
shu

Distributed MPC for Reconfigurable Architecture Systems via Alternating Direction Method of Multipliers

doi: 10.1109/JAS.2020.1003195

  • Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China

Funds:  This work was support by the National Natural Science Foundation of China (61833012, 61773162, 61590924) and the Natural Science Foundation of Shanghai (18ZR1420000)
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    Abstract
  • This paper investigates the distributed model predictive control (MPC) problem of linear systems where the network topology is changeable by the way of inserting new subsystems, disconnecting existing subsystems, or merely modifying the couplings between different subsystems. To equip live systems with a quick response ability when modifying network topology, while keeping a satisfactory dynamic performance, a novel reconfiguration control scheme based on the alternating direction method of multipliers (ADMM) is presented. In this scheme, the local controllers directly influenced by the structure realignment are redesigned in the reconfiguration control. Meanwhile, by employing the powerful ADMM algorithm, the iterative formulas for solving the reconfigured optimization problem are obtained, which significantly accelerate the computation speed and ensure a timely output of the reconfigured optimal control response. Ultimately, the presented reconfiguration scheme is applied to the level control of a benchmark four-tank plant to illustrate its effectiveness and main characteristics.

     

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    Highlights

    • A reconfiguration control strategy is presented in presence of three typical modes;
    • A non-cooperative distributed MPC scheme combined with ADMM algorithm is proposed;
    • A benchmark four-tank plant with reconfigurable architecture is employed.

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