Dynamics and Estimator-Based Nonlinear Control of a PEM Fuel Cell

Abstract

In this paper, an estimator-based nonlinear globally linearizing controller (GLC) is proposed for regulating a multivariable nonlinear proton exchange membrane fuel cell. To represent the actual process, we have adopted a simulated model and then validated it with experimental data. Aiming to formulate a state estimator, the predictor model is derived with a reduced number of model equations with considering only the controlled variables as true states, keeping others as augmented states with no dynamics. Instead of computing all states, which is quite a common phenomenon for most of the estimators, the proposed adaptive state observer (ASO) computes a limited number of states as per the GLC requirement. This, in turn, leads to a large process/model mismatch, the effect of which is attempted to reduce by introducing a variable tuning parameter of ASO. Subsequently, the GLC structure is synthesized with combining a nonlinear transformer (input-output linearizing state feedback), a dual-loop external linear controller, and an adaptive state observer. The superiority of the proposed GLC-ASO scheme is finally shown over a conventional dual-loop proportional-integral controller in terms of set point tracking and disturbance rejection.