Physical modelling of a long pneumatic transmission line: models of successively decreasing complexity and their experimental validation

Richard Kern

Mathematical and Computer Modelling of Dynamical Systems, 2017, vol. 23, issue 5, 536-553

Abstract: There exist a significant number of models, which describe the dynamics of pneumatic transmission lines. The models are based on different assumptions and, thereby, vary in the physical phenomena they incorporate. These assumptions made are not always stated clearly and the models are rarely validated with measurement data. The aim of this article is to present multiple distributed parameter models that, starting from a physical system description, successively decrease in complexity and finally result in a rather simple system representation. Data, both from simulation studies as well as from a pneumatic test bench, serve as a quantitative validation of these assumptions. Based on a detailed discussion of the different models, this article aims at facilitating the choice of an appropriate model for a given task where the effect of long pneumatic transmission lines cannot be neglected and a trade-off between accuracy and complexity is required.

Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/13873954.2017.1282880 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:nmcmxx:v:23:y:2017:i:5:p:536-553

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/NMCM20

DOI: 10.1080/13873954.2017.1282880

Access Statistics for this article

Mathematical and Computer Modelling of Dynamical Systems is currently edited by I. Troch

More articles in Mathematical and Computer Modelling of Dynamical Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().