In this paper we propose a Nonlinear Model Predictive Control (NMPC) scheme for the optimization of the start-up procedure of a nonlinear boiler model. The proposed formulation of the MPC problem allows for a significant reduction of the optimization horizon with respect to state of the art - often open loop - optimization approaches (that commonly solve the nonlinear program for a long horizon that includes the whole start-up time), while guaranteeing the recursive feasibility and remarkable performances. A numerically efficient implementation of NMPC is obtained by subsequent linearisation of the system along the predicted trajectory. Simulation results show the advantages of the proposed method with respect to standard manual procedures and to open-loop optimization approaches.

An optimal control of start-up for nonlinear fire-tube boilers with thermal stress constraints

Stefano Spinelli;Andrea Ballarino
2019

Abstract

In this paper we propose a Nonlinear Model Predictive Control (NMPC) scheme for the optimization of the start-up procedure of a nonlinear boiler model. The proposed formulation of the MPC problem allows for a significant reduction of the optimization horizon with respect to state of the art - often open loop - optimization approaches (that commonly solve the nonlinear program for a long horizon that includes the whole start-up time), while guaranteeing the recursive feasibility and remarkable performances. A numerically efficient implementation of NMPC is obtained by subsequent linearisation of the system along the predicted trajectory. Simulation results show the advantages of the proposed method with respect to standard manual procedures and to open-loop optimization approaches.
2019
Istituto di Sistemi e Tecnologie Industriali Intelligenti per il Manifatturiero Avanzato - STIIMA (ex ITIA)
9783907144008
Nonlinear Model Predictive Control
Linear Time-Varying MPC
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Descrizione: An optimal control of start-up for nonlinear fire-tube boilers with thermal stress constraints
Tipologia: Versione Editoriale (PDF)
Dimensione 2.29 MB
Formato Adobe PDF
2.29 MB Adobe PDF Visualizza/Apri

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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/388032
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