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

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.