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Control Design Based on FMI: A Diesel Engine Control Case Study

Author

Editor

  • Per Tunestål
  • Lars Eriksson

Summary, in English

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.

Publishing year

2016-06-20

Language

English

Pages

231-238

Publication/Series

IFAC-PapersOnLine

Volume

49

Issue

11

Document type

Conference paper

Publisher

IFAC

Topic

  • Control Engineering

Conference name

8th IFAC Symposium Advances in Automotive Control, AAC 2016

Conference date

2016-06-20 - 2016-06-23

Conference place

Sweden

Status

Published

Project

  • Diesel HCCI in a Multi-Cylinder Engine

Research group

  • LCCC