This paper deals with the air management subsystem in fuel cell systems (FCS). It proposes to use a feedforward control action for improving a classical PI control of the FCS for preventing oxygen starvation by using the control scheme suggested by Kawato. This paper therefore, proposes the application of a recent neural network scheme, the GMR (Generalized Mapping Regressor Mapping) to implement a static feedforward controller, which is obtained with the inversion of the FCS model. The idea, for the air management subsystem, is to use a feedforward for optimising a classical PI control of the FCS for preventing oxygen starvation. This control system has been implemented both in numerical simulation and experimentally adopting a properly devised FCS in which the FC stack is realized by a buck-converter (emulator), that is by using a hardware-in-the-loop experimental rig.

A Neural Inverse Control of the PEM-FC Voltage by the Generalized Mapping Regressor (GMR

G Marsala;Pucci M;Vitale G;
2008

Abstract

This paper deals with the air management subsystem in fuel cell systems (FCS). It proposes to use a feedforward control action for improving a classical PI control of the FCS for preventing oxygen starvation by using the control scheme suggested by Kawato. This paper therefore, proposes the application of a recent neural network scheme, the GMR (Generalized Mapping Regressor Mapping) to implement a static feedforward controller, which is obtained with the inversion of the FCS model. The idea, for the air management subsystem, is to use a feedforward for optimising a classical PI control of the FCS for preventing oxygen starvation. This control system has been implemented both in numerical simulation and experimentally adopting a properly devised FCS in which the FC stack is realized by a buck-converter (emulator), that is by using a hardware-in-the-loop experimental rig.
2008
Istituto di Studi sui Sistemi Intelligenti per l'Automazione - ISSIA - Sede Bari
Inglese
The forty-third Annual Meeting of the IEEE Industry Applications Society (IAS 2008) 5-9
1
12
978-1-4244-2279-1
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=4658942&contentType=Conference+Publications&matchBoolean%3Dtrue%26searchField%3DSearch_All%26queryText%3D%28%28%28p_Title%3Aneural%29+AND+p_Title%3Ainverse%29+AND+p_Authors%3Avitale+g.%29
Sì, ma tipo non specificato
5-9 oct 2008
Edmonton, Alberta, Canada
fuel cell systems
air management
neural networks
9
none
G, Marsala; Bouquin, D; Pukrushpan, ; J, T; Pucci, M; Cirrincione, G; Vitale, G; Miraoui, ; A,
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/104226
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 0
social impact