On the significance of the noise model for the performance of a linear MPC in closed-loop operation

Morten Hagdrup; Dimitri Boiroux; Zeinab Mahmoudi; Henrik Madsen; Niels Kjølstad Poulsen; Bjarne Poulsen; John Bagterp Jørgensen

doi:10.1016/j.ifacol.2016.07.241

On the significance of the noise model for the performance of a linear MPC in closed-loop operation

Morten Hagdrup, Dimitri Boiroux, Zeinab Mahmoudi, Henrik Madsen, Niels Kjølstad Poulsen, Bjarne Poulsen, John Bagterp Jørgensen

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Abstract

This paper discusses the significance of the noise model for the performance of a Model Predictive Controller when operating in closed-loop. The process model is parametrized as a continuous-time (CT) model and the relevant sampled-data filtering and control algorithms are developed. Using CT models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

Original language	English
Title of host publication	IFAC-PapersOnLine
Volume	49
Publisher	Elsevier
Publication date	2016
Pages	171-176
DOIs	https://doi.org/10.1016/j.ifacol.2016.07.241
Publication status	Published - 2016
Event	11th IFAC Symposium on Dynamics and Control of Process Systems Including Biosystems DYCOPS-CAB 2016 - Trondheim, Norway Duration: 6 Jun 2016 → 8 Jun 2016 Conference number: 11 http://dycops2016.org/

Conference

Conference	11th IFAC Symposium on Dynamics and Control of Process Systems Including Biosystems DYCOPS-CAB 2016
Number	11
Country/Territory	Norway
City	Trondheim
Period	06/06/2016 → 08/06/2016
Internet address	http://dycops2016.org/

Series	IFAC-PapersOnLine
ISSN	2405-8963

Keywords

Closed-loop control predictive control
Model based control
Kalman Filters
State estimation

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title = "On the significance of the noise model for the performance of a linear MPC in closed-loop operation",

abstract = "This paper discusses the significance of the noise model for the performance of a Model Predictive Controller when operating in closed-loop. The process model is parametrized as a continuous-time (CT) model and the relevant sampled-data filtering and control algorithms are developed. Using CT models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.",

keywords = "Closed-loop control predictive control, Model based control, Kalman Filters, State estimation",

author = "Morten Hagdrup and Dimitri Boiroux and Zeinab Mahmoudi and Henrik Madsen and Poulsen, {Niels Kj{\o}lstad} and Bjarne Poulsen and J{\o}rgensen, {John Bagterp}",

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Hagdrup, M, Boiroux, D, Mahmoudi, Z, Madsen, H, Poulsen, NK, Poulsen, B & Jørgensen, JB 2016, On the significance of the noise model for the performance of a linear MPC in closed-loop operation. in IFAC-PapersOnLine. vol. 49, Elsevier, IFAC-PapersOnLine, pp. 171-176, 11th IFAC Symposium on Dynamics and Control of Process Systems Including Biosystems DYCOPS-CAB 2016 , Trondheim, Norway, 06/06/2016. https://doi.org/10.1016/j.ifacol.2016.07.241

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AU - Poulsen, Niels Kjølstad

AU - Poulsen, Bjarne

AU - Jørgensen, John Bagterp

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N2 - This paper discusses the significance of the noise model for the performance of a Model Predictive Controller when operating in closed-loop. The process model is parametrized as a continuous-time (CT) model and the relevant sampled-data filtering and control algorithms are developed. Using CT models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

AB - This paper discusses the significance of the noise model for the performance of a Model Predictive Controller when operating in closed-loop. The process model is parametrized as a continuous-time (CT) model and the relevant sampled-data filtering and control algorithms are developed. Using CT models typically means less parameters to identify. Systematic tuning of such controllers is discussed. Simulation studies are conducted for linear time-invariant systems showing that choosing a noise model of low order is beneficial for closed-loop performance. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

KW - Closed-loop control predictive control

KW - Model based control

KW - Kalman Filters

KW - State estimation

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ER -

On the significance of the noise model for the performance of a linear MPC in closed-loop operation

Abstract

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Keywords

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