NDLI: Fast Model Predictive Control of PEM Fuel Cell System Using the $L_{1}$ Norm

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Fast Model Predictive Control of PEM Fuel Cell System Using the $L_{1}$ Norm

Content Provider	MDPI
Author	Maciej, Ławryńczuk Nebeluk, Robert
Copyright Year	2022
Abstract	This work describes the development of a fast Model Predictive Control (MPC) algorithm for a Proton Exchange Membrane (PEM) fuel cell. The MPC cost-function used considers the sum of absolute values of predicted control errors (the L $_{1}$ norm). Unlike previous approaches to nonlinear MPC-L $_{1}$ , in which quite complicated neural approximators have been used, two analytical approximators of the absolute value function are utilised. An advanced trajectory linearisation is performed on-line. As a result, an easy-to-solve quadratic optimisation task is derived. All implementation details of the discussed algorithm are detailed for two considered approximators. Furthermore, the algorithm is thoroughly compared with the classical MPC-L $_{2}$ method in which the sum of squared predicted control errors is minimised. A multi-criteria control quality assessment is performed as the MPC-L $_{1}$ and MPC-L $_{2}$ algorithms are compared using four control quality indicators. It is shown that the presented MPC-L $_{1}$ scheme gives better results for the PEM.
Starting Page	5157
e-ISSN	19961073
DOI	10.3390/en15145157
Journal	Energies
Issue Number	14
Volume Number	15
Language	English
Publisher	MDPI
Publisher Date	2022-07-15
Access Restriction	Open
Subject Keyword	Energies Energy and Fuel Technology Proton Exchange Membrane Fuel Cell Model Predictive Control Optimisation L1 Cost Function
Content Type	Text
Resource Type	Article

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