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Volume 6 Issue 5
Sep.  2019

IEEE/CAA Journal of Automatica Sinica

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Article Contents
Shiwen Tong, Dianwei Qian, Xiaoyu Yan, Jianjun Fang and Wei Liu, "Design of a Networked Tracking Control System With a Data-based Approach," IEEE/CAA J. Autom. Sinica, vol. 6, no. 5, pp. 1261-1267, Sept. 2019. doi: 10.1109/JAS.2018.7511093
Citation: Shiwen Tong, Dianwei Qian, Xiaoyu Yan, Jianjun Fang and Wei Liu, "Design of a Networked Tracking Control System With a Data-based Approach," IEEE/CAA J. Autom. Sinica, vol. 6, no. 5, pp. 1261-1267, Sept. 2019. doi: 10.1109/JAS.2018.7511093

Design of a Networked Tracking Control System With a Data-based Approach

doi: 10.1109/JAS.2018.7511093
Funds:

the National Natural Science Foundation of China 51205025

the National Natural Science Foundation of China 51775048

the National Natural Science Foundation of China 61602041

the Science and Technology Program of Beijing Municipal Education Commission KM201611417009

the Science and Technology Program of Beijing Municipal Education Commission KM201811417001

the Premium Funding Project for Academic Human Resources Development in Beijing Union University (BUU) BPHR2017CZ08

the Beijing Natural Science FoundationBeijing Municipal Education Commission Joint Fund KZ201811417048

the Project of 2018-2019 Basic Research Fund of BUU, the Beijing Advanced Innovation Center for Intelligent Robots and Systems Open Fund 2018I RS17

the Project of Beijing Municipal Natural Science Foundation 4142018

the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions CIT & TCD20150314

More Information
  • Tracking control is a very challenging problem in the networked control system (NCS), especially for the process with blurred mechanism and where only input-output data are available. This paper has proposed a data-based design approach for the networked tracking control system (NTCS). The method utilizes the input-output data of the controlled process to establish a predictive model with the help of fuzzy cluster modelling (FCM) technology. Then, the deduced error and error change in the future are treated as inputs of a fuzzy sliding mode controller (FSMC) to obtain a string of future control actions. These candidate control actions in the controller side are delivered to the plant side. Thus, the network induced time delays are compensated by selecting appropriate control action. Simulation outputs prove the validity of the proposed method.

     

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    Highlights

    • Data-based design method which is started from the input-output data of the process with fuzzy cluster modeling technology is proposed.
    • Predicted control actions from the transmitted data packet, which is based on the future errors and error changes, are utillized to compensate for the time-delay in the network.
    • Implicit predictive model has been transformed into an explicit form by means of neural network approximation.
    • Fuzzy sliding mode controller oriented to future control actions is designed.

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