Data-reconciliation based fault-tolerant model predictive control for a biomass boiler

Palash Sarkar*, Jukka Kortela, Alexandre Boriouchkine, Elena Zattoni, Sirkka Liisa Jämsä-Jounela

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

3 Sitaatiot (Scopus)
159 Lataukset (Pure)

Abstrakti

This paper presents a novel, effective method to handle critical sensor faults affecting a control system devised to operate a biomass boiler. In particular, the proposed method consists of integrating a data reconciliation algorithm in a model predictive control loop, so as to annihilate the effects of faults occurring in the sensor of the flue gas oxygen concentration, by feeding the controller with the reconciled measurements. Indeed, the oxygen content in flue gas is a key variable in control of biomass boilers due its close connections with both combustion efficiency and polluting emissions. The main benefit of including the data reconciliation algorithm in the loop, as a fault tolerant component, with respect to applying standard fault tolerant methods, is that controller reconfiguration is not required anymore, since the original controller operates on the restored, reliable data. The integrated data reconciliation-model predictive control (MPC) strategy has been validated by running simulations on a specific type of biomass boiler - the KPA Unicon BioGrate boiler.

AlkuperäiskieliEnglanti
Artikkeli194
Sivut1-14
Sivumäärä14
JulkaisuEnergies
Vuosikerta10
Numero2
DOI - pysyväislinkit
TilaJulkaistu - 2017
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

Sormenjälki Sukella tutkimusaiheisiin 'Data-reconciliation based fault-tolerant model predictive control for a biomass boiler'. Ne muodostavat yhdessä ainutlaatuisen sormenjäljen.

  • Laitteet

  • Siteeraa tätä