Parameter estimation of a microbial fuel cell process control-oriented model

Microbial fuel cells (MFCs) are novel devices capable of producing electricity while cleaning wastewater. Developing dynamic control-oriented models for such systems represents a crucial tool for the future design of software sensors and model-based control strategies. To this end, this work presents a MFC process control-oriented model obtained by combining fundamental equations based on mass and electron balances with equations describing an equivalent electrical circuit. Such model accounts for the double layer capacitance effect and complex nonlinear dynamics observed during pulse-width modulated operation of the external resistance and therefore, it is able to describe the observed biological or long-term dynamics as well as the electrical or short-term dynamics. The parameter estimation for a simulation and a prediction MFC process control-oriented model is here described.