A Multivariable Nonlinear Model Predictive Control Framework for a PEM Fuel Cell System
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The aim of this work is to present an integrated framework for the on-line control of a Polymer Electrolyte Membrane (PEM) fuel cell system using an optimization-based control methodology. The framework consists of a nonlinear model predictive control (NMPC) scheme and an on-line supervisory control and data acquisition system (SCADA). The solution of the NMPC problem is achieved by a direct optimization method which involves the use of orthogonal collocation on finite elements and represents the optimal control problem as a nonlinear programming problem (NLP). The on-line application of the multivariable controller shows that the proposed framework can accomplish the desired objectives for power fulfilment in the context of a safe operating region. Furthermore the controller exhibits excellent performance in terms of computational requirements and can follow load changes with a negligible error in its response. 2012 Elsevier B.V.