Semi-parametric Regression based on Machine Learning Methods for UAS Stall Identification. Issue 7 (2021)

• Record Type: Journal Article
• Authors: Guibert, Vincent; Brunot, Mathieu; Bronz, Murat; Condomines, Jean-Philippe
• Is Part Of: IFAC-PapersOnLine. Volume 54:Issue 7(2021)
• Page Start: 180
• Page End: 185
• Publication Date: 2021
• Subjects: Nonlinear system identification -- Machine learning -- Grey box modelling -- Unmanned aircraft system -- Stall modelling -- Non-parametric methods; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2021.08.355
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: A semi-parametric regression methodology is formulated to identify the unsteady lift characteristics of a small UAS undergoing dynamic stall. Based on the trailing edge separation model of Leishmann and Beddoes, the nonlinear evolution of the separation point is formulated so that it can be estimated by non-parametric Machine Learning methods. Validation of the methodology is presented with the identification of the lift coefficient based on quasi-steady wind tunnel tests.