A Numerical Study of the Robustness of Transcription Methods for Parameter Identification Problems. Issue 1 (17th December 2018)

• Record Type: Journal Article
• Authors: Schäfer, Kai; Flaßkamp, Kathrin; Büskens, Christof
• Other Names: Müller G. guestEditor.; Ulbrich M. guestEditor.
• Is Part Of: Proceedings in applied mathematics and mechanics. Volume 18:Issue 1(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-12-17
• Subjects: Applied mathematics -- Periodicals; Engineering mathematics -- Periodicals; Mathematical physics -- Periodicals; 519
• DOI: 10.1002/pamm.201800101
• Languages: English
• ISSNs: 1617-7061

Abstract

Abstract: In this work, we apply transcription methods known from optimal control to nonlinear dynamic parameter identification problems. We analyze and compare the methods with the help of an application example from robotics. More specifically, we investigate their robustness against varying initial parameters and show numerically, that an increasing number of variables leads to a more robust optimization behavior and qualitatively better solutions.