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Automation and Remote Control

, Volume 79, Issue 12, pp 2159–2168 | Cite as

Identification of Piecewise Linear Parameters of Regression Models of Non-Stationary Deterministic Systems

  • Jian Wang
  • Tuan Le Vang
  • A. A. Pyrkin
  • S. A. Kolyubin
  • A. A. Bobtsov
Stochastic Systems
  • 13 Downloads

Abstract

We consider the problem of identifying unknown nonstationary piecewise linear parameters for a linear regression model. A new algorithm is proposed that allows, in the case of a number of assumptions on the elements of the regressor, to provide an estimate of unknown non-stationary parameters. We analyze in detail the case with two unknown parameters, which makes it possible to understand the main idea of the proposed approach. We also consider a generalization to the case of an arbitrary number of parameters. We give an example of computer simulation that illustrates the efficiency of the proposed approach.

Keywords

identification sensorless control biomechatronic systems linear regression model dynamic regressor expansion 

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Copyright information

© Pleiades Publishing, Inc. 2018

Authors and Affiliations

  • Jian Wang
    • 1
  • Tuan Le Vang
    • 2
  • A. A. Pyrkin
    • 2
  • S. A. Kolyubin
    • 2
  • A. A. Bobtsov
    • 2
  1. 1.Hangzhou Dianzi UniversityHangzhouChina
  2. 2.ITMO University (National Research University of Information Technologies, Mechanics and Optics)St. PetersburgRussia

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