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Energies 2017, 10(2), 194; doi:10.3390/en10020194

Data-Reconciliation Based Fault-Tolerant Model Predictive Control for a Biomass Boiler

1
Department of Biotechnology and Chemical Technology, School of Chemical Engineering, Aalto University, 00076 Aalto, Finland
2
Department of Electrical, Electronic and Information Engineering “G. Marconi”, Alma Mater Studiorum · University of Bologna, 40136 Bologna, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Tariq Al-Shemmeri
Received: 26 September 2016 / Revised: 22 January 2017 / Accepted: 25 January 2017 / Published: 9 February 2017
(This article belongs to the Special Issue Biomass for Energy Country Specific Show Case Studies)
View Full-Text   |   Download PDF [2094 KB, uploaded 9 February 2017]   |  

Abstract

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. View Full-Text
Keywords: data reconciliation; model predictive control; fault-tolerant contro; BioGrate boiler data reconciliation; model predictive control; fault-tolerant contro; BioGrate boiler
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MDPI and ACS Style

Sarkar, P.; Kortela, J.; Boriouchkine, A.; Zattoni, E.; Jämsä-Jounela, S.-L. Data-Reconciliation Based Fault-Tolerant Model Predictive Control for a Biomass Boiler. Energies 2017, 10, 194.

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