Data-driven predictive control for networked control systems

  • Authors:

  • Yuanqing Xia;Wen Xie;Bo Liu;Xiaoyun Wang

  • Affiliations:

  • School of Automation, Beijing Institute of Technology, Beijing 100081, China and Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing 100081, China;School of Automation, Beijing Institute of Technology, Beijing 100081, China and Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing 100081, China;School of Automation, Beijing Institute of Technology, Beijing 100081, China and Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing 100081, China;School of Automation, Beijing Institute of Technology, Beijing 100081, China and Key Laboratory of Intelligent Control and Decision of Complex Systems, Beijing 100081, China

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2013

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Abstract

This paper is concerned with the problem of data-driven predictive control for networked control systems (NCSs), which is designed by applying the subspace matrices technique, obtained directly from the input/output data transferred from networks. The networked predictive control consists of the control prediction generator and network delay compensator. The control prediction generator provides a set of future control predictions to make the closed-loop system achieve the desired control performance and the network delay compensator eliminates the effects of the network transmission delay. The effectiveness and superiority of the proposed method is demonstrated in simulation as well as experiment study.