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Research Papers

# A Review of Proper Modeling Techniques

[+] Author and Article Information
Tulga Ersal

Department of Mechanical Engineering, The University of Michigan, Ann Arbor, MI 48109tersal@umich.edu

Hosam K. Fathy

Department of Mechanical Engineering, The University of Michigan, Ann Arbor, MI 48109hfathy@umich.edu

D. Geoff Rideout

Department of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canadagrideout@engr.mun.ca

Loucas S. Louca

Department of Mechanical and Manufacturing Engineering, University of Cyprus, Nicosia 1678, Cypruslslouca@ucy.ac.cy

Jeffrey L. Stein

Department of Mechanical Engineering, The University of Michigan, Ann Arbor, MI 48109stein@umich.edu

J. Dyn. Sys., Meas., Control 130(6), 061008 (Sep 25, 2008) (13 pages) doi:10.1115/1.2977484 History: Received December 14, 2007; Revised June 13, 2008; Published September 25, 2008

## Abstract

A dynamic system model is proper for a particular application if it achieves the accuracy required by the application with minimal complexity. Because model complexity often—but not always—correlates inversely with simulation speed, a proper model is often alternatively defined as one balancing accuracy and speed. Such balancing is crucial for applications requiring both model accuracy and speed, such as system optimization and hardware-in-the-loop simulation. Furthermore, the simplicity of proper models conduces to control system analysis and design, particularly given the ease with which lower-order controllers can be implemented compared to higher-order ones. The literature presents many algorithms for deducing proper models from simpler ones or reducing complex models until they become proper. This paper presents a broad survey of the proper modeling literature. To simplify the presentation, the algorithms are classified into frequency, projection, optimization, and energy based, based on the metrics they use for obtaining proper models. The basic mechanics, properties, advantages, and limitations of the methods are discussed, along with the relationships between different techniques, with the intention of helping the modeler to identify the most suitable proper modeling method for a given application.

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