Control Design Based on FMI: A Diesel Engine Control Case Study
Nylén, Anders ; Henningsson, Maria ; Cervin, Anton LU
and Tunestål, Per
LU
(2016)
8th IFAC Symposium Advances in Automotive Control, AAC 2016
In IFAC-PapersOnLine
49(11).
p.231-238
- Abstract
- Modelica allows systems to be described with reuseable components and with a high precision. To be able to use such complex models efficiently, high demands are set on tools that allow the user to extract the information needed from the models in a straight-forward manner. For this purpose, design-of-experiments techniques can be used to systematically analyze the complex models.
In this paper, it is demonstrated how a Modelica model of a diesel engine can be used for control design. The engine model has multiple inputs and outputs, it is nonlinear, has many parameters, and has a higher order than most control design algorithms are able to handle in a numerically robust way.
It is shown how the features for dynamic... (More) - Modelica allows systems to be described with reuseable components and with a high precision. To be able to use such complex models efficiently, high demands are set on tools that allow the user to extract the information needed from the models in a straight-forward manner. For this purpose, design-of-experiments techniques can be used to systematically analyze the complex models.
In this paper, it is demonstrated how a Modelica model of a diesel engine can be used for control design. The engine model has multiple inputs and outputs, it is nonlinear, has many parameters, and has a higher order than most control design algorithms are able to handle in a numerically robust way.
It is shown how the features for dynamic design-of-experiments analysis in the FMI Toolbox for MATLAB can be used to analyze the variation in system dynamics across the engine operating range. A gain scheduling of nine multivariable linear-quadratic-gaussian (LQG) controllers, is designed based on linearization and model reduction of the original nonlinear FMU model. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/3f87b975-3aa7-4664-981f-424d1baca2fe
- author
- Nylén, Anders
; Henningsson, Maria
; Cervin, Anton
LU
and Tunestål, Per
LU
- organization
- publishing date
- 2016-06-20
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 8th IFAC Symposium on Advances in Automotive Control AAC 2016
- series title
- IFAC-PapersOnLine
- editor
- Tunestål, Per and Eriksson, Lars
- volume
- 49
- issue
- 11
- pages
- 231 - 238
- publisher
- IFAC
- conference name
- 8th IFAC Symposium Advances in Automotive Control, AAC 2016
- conference location
- Sweden
- conference dates
- 2016-06-20 - 2016-06-23
- external identifiers
-
- scopus:84991111410
- wos:000383464400035
- DOI
- 10.1016/j.ifacol.2016.08.035
- project
- Diesel HCCI in a Multi-Cylinder Engine
- language
- English
- LU publication?
- yes
- id
- 3f87b975-3aa7-4664-981f-424d1baca2fe
- date added to LUP
- 2016-08-16 09:27:09
- date last changed
- 2022-01-30 18:09:49
@inproceedings{3f87b975-3aa7-4664-981f-424d1baca2fe,
abstract = {{Modelica allows systems to be described with reuseable components and with a high precision. To be able to use such complex models efficiently, high demands are set on tools that allow the user to extract the information needed from the models in a straight-forward manner. For this purpose, design-of-experiments techniques can be used to systematically analyze the complex models.<br/>In this paper, it is demonstrated how a Modelica model of a diesel engine can be used for control design. The engine model has multiple inputs and outputs, it is nonlinear, has many parameters, and has a higher order than most control design algorithms are able to handle in a numerically robust way.<br/><br/>It is shown how the features for dynamic design-of-experiments analysis in the FMI Toolbox for MATLAB can be used to analyze the variation in system dynamics across the engine operating range. A gain scheduling of nine multivariable linear-quadratic-gaussian (LQG) controllers, is designed based on linearization and model reduction of the original nonlinear FMU model.}},
author = {{Nylén, Anders and Henningsson, Maria and Cervin, Anton and Tunestål, Per}},
booktitle = {{8th IFAC Symposium on Advances in Automotive Control AAC 2016}},
editor = {{Tunestål, Per and Eriksson, Lars}},
language = {{eng}},
month = {{06}},
number = {{11}},
pages = {{231--238}},
publisher = {{IFAC}},
series = {{IFAC-PapersOnLine}},
title = {{Control Design Based on FMI: A Diesel Engine Control Case Study}},
url = {{http://dx.doi.org/10.1016/j.ifacol.2016.08.035}},
doi = {{10.1016/j.ifacol.2016.08.035}},
volume = {{49}},
year = {{2016}},
}