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

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    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.
    Original languageEnglish
    Pages (from-to)39-60
    JournalFuzzy Sets and Systems
    Volume248
    DOIs
    Publication statusPublished - 1 Aug 2014

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Research Keywords

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

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