Self-Tuning Linear Quadratic Supervisory Regulation of a Diesel Generator using Large-Signal State Estimation

Jesper Viese Knudsen; Jan Dimon Bendtsen; Palle Andersen; Kjeld Madsen

doi:10.1109/AUCC.2016.7867928

Self-Tuning Linear Quadratic Supervisory Regulation of a Diesel Generator using Large-Signal State Estimation

Jesper Viese Knudsen, Jan Dimon Bendtsen, Palle Andersen, Kjeld Madsen

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

2 Citations (Scopus)

Abstract

In this paper, a self-tuning linear quadratic supervisory regulator using a large-signal state estimator for a diesel driven generator set is proposed. The regulator improves operational efficiency, in comparison to current implementations, by (i) automating the initial tuning process and (ii) enabling automated retuning capabilities. Utilizing a first principles-based nonlinear model detailed in [1], the procedure is demonstrated through simulations after real system measurements have been used for parameter identification. The regulator is able to suppress load-induced variations successfully throughout the operating range of the diesel generator.

Original language	English
Title of host publication	Australian Control Conference (AUCC) 2016
Number of pages	6
Publisher	IEEE
Publication date	2016
ISBN (Print)	978-1-5090-5764-1
ISBN (Electronic)	978-1-922107-90-9
DOIs	https://doi.org/10.1109/AUCC.2016.7867928
Publication status	Published - 2016
Event	The 2016 Australian Control Conference - Newcastle, Australia Duration: 3 Nov 2016 → 4 Nov 2016 http://www.aucc2016.org.au/

Conference

Conference	The 2016 Australian Control Conference
Country/Territory	Australia
City	Newcastle
Period	03/11/2016 → 04/11/2016
Internet address	http://www.aucc2016.org.au/

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title = "Self-Tuning Linear Quadratic Supervisory Regulation of a Diesel Generator using Large-Signal State Estimation",

abstract = "In this paper, a self-tuning linear quadratic supervisory regulator using a large-signal state estimator for a diesel driven generator set is proposed. The regulator improves operational efficiency, in comparison to current implementations, by (i) automating the initial tuning process and (ii) enabling automated retuning capabilities. Utilizing a first principles-based nonlinear model detailed in [1], the procedure is demonstrated through simulations after real system measurements have been used for parameter identification. The regulator is able to suppress load-induced variations successfully throughout the operating range of the diesel generator.",

author = "Knudsen, {Jesper Viese} and Bendtsen, {Jan Dimon} and Palle Andersen and Kjeld Madsen",

year = "2016",

doi = "10.1109/AUCC.2016.7867928",

language = "English",

isbn = "978-1-5090-5764-1",

booktitle = "Australian Control Conference (AUCC) 2016",

publisher = "IEEE",

address = "United States",

note = "The 2016 Australian Control Conference, AUCC 2016 ; Conference date: 03-11-2016 Through 04-11-2016",

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T1 - Self-Tuning Linear Quadratic Supervisory Regulation of a Diesel Generator using Large-Signal State Estimation

AU - Knudsen, Jesper Viese

AU - Bendtsen, Jan Dimon

AU - Andersen, Palle

AU - Madsen, Kjeld

PY - 2016

Y1 - 2016

N2 - In this paper, a self-tuning linear quadratic supervisory regulator using a large-signal state estimator for a diesel driven generator set is proposed. The regulator improves operational efficiency, in comparison to current implementations, by (i) automating the initial tuning process and (ii) enabling automated retuning capabilities. Utilizing a first principles-based nonlinear model detailed in [1], the procedure is demonstrated through simulations after real system measurements have been used for parameter identification. The regulator is able to suppress load-induced variations successfully throughout the operating range of the diesel generator.

AB - In this paper, a self-tuning linear quadratic supervisory regulator using a large-signal state estimator for a diesel driven generator set is proposed. The regulator improves operational efficiency, in comparison to current implementations, by (i) automating the initial tuning process and (ii) enabling automated retuning capabilities. Utilizing a first principles-based nonlinear model detailed in [1], the procedure is demonstrated through simulations after real system measurements have been used for parameter identification. The regulator is able to suppress load-induced variations successfully throughout the operating range of the diesel generator.

U2 - 10.1109/AUCC.2016.7867928

DO - 10.1109/AUCC.2016.7867928

M3 - Article in proceeding

SN - 978-1-5090-5764-1

BT - Australian Control Conference (AUCC) 2016

PB - IEEE

T2 - The 2016 Australian Control Conference

Y2 - 3 November 2016 through 4 November 2016

ER -

Self-Tuning Linear Quadratic Supervisory Regulation of a Diesel Generator using Large-Signal State Estimation

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