Quasi-min-max fuzzy model predictive control of direct methanol fuel cells

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

8 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)39-60
Journal / PublicationFuzzy Sets and Systems
Volume248
Publication statusPublished - 1 Aug 2014

Abstract

Direct methanol fuel cells (DMFCs) are known as a promising power source in future. In this paper, we consider steering a DMFC plant to a desired operating point while optimizing the transient performance according to a quadratic cost function. Quasi-min-max fuzzy model predictive control (FMPC) with input constraints is proposed for the DMFC. In order to reduce the computational burden for real time implementation, a partial off-line quasi-min-max FMPC is also proposed. In this case, a bank of invariant sets together with the corresponding feedback control laws are obtained by solving some linear matrix inequalities (LMIs) off-line, leaving the online part a bisection search and a much simplified constrained optimization problem. Online computation complexity for both the quasi-min-max FMPC and the partial off-line one is also analyzed. Simulation results are given to show the effectiveness of the proposed controllers. © 2013 Elsevier B.V.

Research Area(s)

  • DMFC, Fuzzy control, Model predictive control, Off-line computation