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Article

Investigating Data-Driven Systems as Digital Twins: Numerical Behavior of Ho–Kalman Method for Order Estimation

Laboratory for Manufacturing Systems and Automation (LMS), Department of Mechanical Engineering and Aeronautics, University of Patras, 265 04 Patras, Greece
Processes 2020, 8(4), 431; https://doi.org/10.3390/pr8040431
Received: 25 February 2020 / Revised: 26 March 2020 / Accepted: 31 March 2020 / Published: 5 April 2020
System identification has been a major advancement in the evolution of engineering. As it is by default the first step towards a significant set of adaptive control techniques, it is imperative for engineers to apply it in order to practice control. Given that system identification could be useful in creating a digital twin, this work focuses on the initial stage of the procedure by discussing simplistic system order identification. Through specific numerical examples, this study constitutes an investigation on the most “natural” method for estimating the order from responses in a convenient and seamless way in time-domain. The method itself, originally proposed by Ho and Kalman and utilizing linear algebra, is an intuitive tool retrieving information out of the data themselves. Finally, with the help of the limitations of the methods, the potential future outlook is discussed, under the prism of forming a digital twin. View Full-Text
Keywords: digital twin; system identification; system order; manufacturing process digital twin; system identification; system order; manufacturing process
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MDPI and ACS Style

Papacharalampopoulos, A. Investigating Data-Driven Systems as Digital Twins: Numerical Behavior of Ho–Kalman Method for Order Estimation. Processes 2020, 8, 431. https://doi.org/10.3390/pr8040431

AMA Style

Papacharalampopoulos A. Investigating Data-Driven Systems as Digital Twins: Numerical Behavior of Ho–Kalman Method for Order Estimation. Processes. 2020; 8(4):431. https://doi.org/10.3390/pr8040431

Chicago/Turabian Style

Papacharalampopoulos, Alexios. 2020. "Investigating Data-Driven Systems as Digital Twins: Numerical Behavior of Ho–Kalman Method for Order Estimation" Processes 8, no. 4: 431. https://doi.org/10.3390/pr8040431

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