Robust iterative learning control for linear systems with multiple time-invariant parametric uncertainties

Hoa Dinh Nguyen, David Banjerdpongchai

Research output: Contribution to journalArticle

Abstract

This article presents a novel robust iterative learning control algorithm (ILC) for linear systems in the presence of multiple time-invariant parametric uncertainties.The robust design problem is formulated as a min-max problem with a quadratic performance criterion subject to constraints of the iterative control input update. Then, we propose a new methodology to find a sub-optimal solution of the min-max problem. By finding an upper bound of the worst-case performance, the min-max problem is relaxed to be a minimisation problem. Applying Lagrangian duality to this minimisation problem leads to a dual problem which can be reformulated as a convex optimisation problem over linear matrix inequalities (LMIs). An LMI-based ILC algorithm is given afterward and the convergence of the control input as well as the system error are proved. Finally, we apply the proposed ILC to a generic example and a distillation column. The numerical results reveal the effectiveness of the LMI-based algorithm.

Original languageEnglish
Pages (from-to)2506-2518
Number of pages13
JournalInternational Journal of Control
Volume83
Issue number12
DOIs
Publication statusPublished - Dec 1 2010
Externally publishedYes

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Linear systems
Linear matrix inequalities
Convex optimization
Distillation columns
Uncertainty

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications

Cite this

Robust iterative learning control for linear systems with multiple time-invariant parametric uncertainties. / Nguyen, Hoa Dinh; Banjerdpongchai, David.

In: International Journal of Control, Vol. 83, No. 12, 01.12.2010, p. 2506-2518.

Research output: Contribution to journalArticle

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