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Evolving Systems

, Volume 10, Issue 2, pp 111–128 | Cite as

Partial identification and control of MIMO systems via switching linear reduced-order models under weak stimulations

  • Saeed Ansari-Rad
  • Ahmad KalhorEmail author
  • Babak N. Araabi
Original Paper
  • 85 Downloads

Abstract

In closed loop identification of an unknown control system, the stability is a big concern particularly when the system does not proceed with sufficient excitation. In this paper, under insufficient excitation of the system, identification and control are investigated by employing Evolving Linear Models (ELMs). It is explained that under weak stimulation, linear correlations between input and output signals and their derivations are occurred. Removing some correlated variables through the time, an equivalent reduced order model of the original system is appeared, which can be identified as an ELM. Defining control law based on the sliding mode control (SMC) and using appropriate adaptation rules for parameters of the model, the tracking errors converge to zero and the stability of the system is guaranteed. Then, convergence of the parameters to their true values is studied and discussed. Different simulations are given to demonstrate the efficacy of the proposed closed loop identification approach.

Keywords

Evolving linear models Reduced-order models Weak stimulation Closed loop identification Sliding mode control 

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Saeed Ansari-Rad
    • 1
  • Ahmad Kalhor
    • 1
    Email author
  • Babak N. Araabi
    • 1
  1. 1.Control and Intelligent Processing Center of Excellence, School of Electrical and Computer EngineeringUniversity of TehranTehranIran

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