# title
A Multivariable Nonlinear Model Predictive Control Framework for a PEM Fuel Cell System

# abstract
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.

# publicationOutlet
11TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING, PTS A AND B

# authors[].organizations[].label
Texas A&M Engineering Experiment Station (TEES)

# keywords[]
On-line Implementation Nonlinear Model Predictive Control

# authorList[]
Ziogou, C., Pistikopoulos, E. N., Voutetakis, S., Georgiadis, M. C., & Papadopoulou, S.