It is proven that the dynamic model of fuel cells is a differentially flat one which means that all its state variables and control inputs can be expressed as differential functions of specific stare variables which are the so-called flat outputs of the system. By exploiting the differential flatness properties of the model its transformation to an equivalent linear form (canonical Brinovsky form) becomes possible. For the latter description of the system's dynamics the design of a state-feedback controller is achieved. This control scheme should be also robust to model uncertainties and external perturbations. To cope with this problem the state-space description of the PEM fuel cells is extended by considering as additional state variables the derivatives of the aggregate disturbance input. Next, a Kalman Filter-based disturbance observer is applied to the linearized extended model of the fuel cells. This estimation method enables to identify the disturbance and model uncertainty terms that affect the system and to introduce a complementary control element that compensates for the perturbations' effects.

A PEM fuel cells control approach based on differential flatness theory

Rigatos, Gerasimos;SIANO, PIERLUIGI
2016-01-01

Abstract

It is proven that the dynamic model of fuel cells is a differentially flat one which means that all its state variables and control inputs can be expressed as differential functions of specific stare variables which are the so-called flat outputs of the system. By exploiting the differential flatness properties of the model its transformation to an equivalent linear form (canonical Brinovsky form) becomes possible. For the latter description of the system's dynamics the design of a state-feedback controller is achieved. This control scheme should be also robust to model uncertainties and external perturbations. To cope with this problem the state-space description of the PEM fuel cells is extended by considering as additional state variables the derivatives of the aggregate disturbance input. Next, a Kalman Filter-based disturbance observer is applied to the linearized extended model of the fuel cells. This estimation method enables to identify the disturbance and model uncertainty terms that affect the system and to introduce a complementary control element that compensates for the perturbations' effects.
2016
9781509020676
9781509020676
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4675775
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