Data-Driven Control With Input Design-Based Data Dropout Compensation for Networked Nonlinear Systems

Zhong-Hua Pang*, G-P Liu, Donghua Zhou, Dehui Sun

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

This brief investigates the regulation problem for a class of networked nonlinear systems with measurement noise, where random data dropouts in both the feedback and forward channels are considered. To actively compensate for the two-channel data dropouts, a data-driven networked compensation control method is proposed, which consists of two aspects: 1) to calculate a control increment based on the measured output error in the controller and 2) to design a data dropout compensation strategy based on the latest control increment available in the actuator. The proposed method merely depends on the input and output data of the controlled plant, without using explicit or implicit information of its mathematical model. Moreover, only one control command needs to be transmitted in the forward channel at each time instant. A sufficient condition is derived to guarantee the closed-loop stability and output error convergence. Both numerical simulations and experimental tests are conducted to demonstrate the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)628-636
Number of pages9
JournalIEEE Transactions on Control Systems Technology
Volume25
Issue number2
Early online date8 Feb 2017
DOIs
Publication statusE-pub ahead of print - 8 Feb 2017

Keywords

  • Data dropout compensation
  • data-driven control
  • measurement noise
  • networked control systems (NCSs)
  • nonlinear systems
  • stability analysis
  • PACKETIZED PREDICTIVE CONTROL
  • OUTPUT TRACKING CONTROL
  • STABILITY ANALYSIS
  • CHANNELS
  • LOSSES

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