Authors: Fatemeh Davoudi; Oliver Lenord; Niklas Worschech; Umut Durak; Sven Hartmann
Addresses: Institute of Informatics, Clausthal University of Technology, Germany ' Department of Virtual Prototypes and Simulation, Robert Bosch GmbH, Germany ' Engineering Systems and Solutions, Bosch Rexroth, Germany ' Institute of Flight Systems, German Aerospace Center (DLR), Germany ' Institute of Informatics, Clausthal University of Technology, Germany
Abstract: Even in times of a continuously growing computational power and miniaturisation of computers and control devices, the demand for model reduction techniques persists. Detailed models of physical systems typically result in rather complex dynamic models. In the design process, when the design space has been narrowed down to a concrete design, it is often desirable to replace these detailed models by simpler ones. The reduced models are expected to run multitudes faster while preserving important properties of the original model required for control design and validation purposes. For evaluation purposes, the reduction method is applied to a simple sample model (two mass spring damper). The reduced model generated by the reduction algorithm is compared with the results of a theoretically derived reduced model. In the conclusions, deficits of the current implementation are discussed. Proposals for further improvements of the methodology for extended control design use cases are given in the outlook.
Keywords: model reduction; parametric model reduction; nonlinear model reduction; proper model generation; Modelica; OpenModelica; residual ranking.
International Journal of Engineering Systems Modelling and Simulation, 2019 Vol.11 No.3, pp.91 - 101
Received: 18 Sep 2018
Accepted: 12 May 2019
Published online: 26 Nov 2019 *