Explicit Nonlinear Model Predictive Control of a Two-Chamber Microbial Fuel Cell

Microbial fuel cells (MFCs) are pollutant removal units which use microorganisms for substrate oxidization and production of electrical energy. A MFC is a nonlinear dynamic system with strong coupling between the variables. This makes the Nonlinear Model Predictive Control (NMPC) approach suitable for the optimal control of this complex plant. In this paper, an approximate multi-parametric nonlinear programming approach is applied to design an explicit NMPC for a two-chamber MFC. The benefits of the explicit predictive controller include efficient on-line computations and simple software and hardware implementation.