Adaptive control for input-constrained linear systems

Bong Seok Park, Jae Young Lee, Jin Bae Park, Yoon Ho Choi

Research output: Contribution to journalArticle

7 Citations (Scopus)

Abstract

This paper proposes a direct model reference adaptive control method for linear systems with unknown parameters in the presence of input constraints. First, we used the well-known linear quadratic regulator (LQR) technique to develop a modified reference model, which is the optimal model under input constraints. Second, a model reference adaptive controller, which tracked the modified reference model instead of the reference model, was designed to compensate for parametric uncertainties. Using Lyapunov stability theory, we proved that the modified reference model tracking error converges to zero. Simulation results demonstrate the effectiveness of the proposed controller.

Original languageEnglish
Pages (from-to)890-896
Number of pages7
JournalInternational Journal of Control, Automation and Systems
Volume10
Issue number5
DOIs
Publication statusPublished - 2012 Oct 1

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Linear systems
Model reference adaptive control
Controllers

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Park, Bong Seok ; Lee, Jae Young ; Park, Jin Bae ; Choi, Yoon Ho. / Adaptive control for input-constrained linear systems. In: International Journal of Control, Automation and Systems. 2012 ; Vol. 10, No. 5. pp. 890-896.
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Adaptive control for input-constrained linear systems. / Park, Bong Seok; Lee, Jae Young; Park, Jin Bae; Choi, Yoon Ho.

In: International Journal of Control, Automation and Systems, Vol. 10, No. 5, 01.10.2012, p. 890-896.

Research output: Contribution to journalArticle

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