A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Volume 6 Issue 1
Jan.  2019

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Ting Bai, Shaoyuan Li and Yi Zheng, "Distributed Model Predictive Control for Networked Plant-wide Systems With Neighborhood Cooperation," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 108-117, Jan. 2019. doi: 10.1109/JAS.2019.1911333
Citation: Ting Bai, Shaoyuan Li and Yi Zheng, "Distributed Model Predictive Control for Networked Plant-wide Systems With Neighborhood Cooperation," IEEE/CAA J. Autom. Sinica, vol. 6, no. 1, pp. 108-117, Jan. 2019. doi: 10.1109/JAS.2019.1911333

Distributed Model Predictive Control for Networked Plant-wide Systems With Neighborhood Cooperation

doi: 10.1109/JAS.2019.1911333
Funds:

the National Nature Science Foundation of China 61590924

the National Nature Science Foundation of China 61673273

the National Nature Science Foundation of China 61833012

More Information
  • For large-scale networked plant-wide systems composed by physically (or geographically) divided subsystems, only limited information is available for local controllers on account of region and communication restrictions. Concerning the optimal control problem of such subsystems, a neighbor-based distributed model predictive control (NDMPC) strategy is presented to improve the global system performance. In this scheme, the performance index of local subsystems and that of its neighbors are minimized together in the determination of the optimal control input, which makes the local control decision also beneficial to its neighboring subsystems and further contributes to improving the convergence and control performance of overall system. The stability of the closed-loop system is proved. Moreover, the parameter designing method for distributed synthesis is provided. Finally, the simulation results illustrate the main characteristics and effectiveness of the proposed control scheme.

     

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