Abstract: Microbial fuel cell is a kind of promising new source of green energy. Because of its complicated reaction mechanism and its inherent characteristics of time-varying, uncertainty, strong-coupling and nonlinearity, there are complex control challenges in modelling and control of microbial fuel cells. This paper studies on performance improvement of microbial fuel cells by the approach of model predictive control. A numerical simulation platform for microbial fuel cell is established, and a traditional model predictive controller is designed for MFC first; then model predictive controllers which use Laguerre function and exponential data weighting are designed subsequently to compare with the traditional model predictive controller. Simulation results show that the proposed improved model predictive controller modified by exponential data weighting can give the system both good steady-state behaviour and satisfactory dynamic property.
Keywords: Microbial fuel cell; Model predictive control; Exponential data weighting; Constant voltage transmission
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