@article{Cunis2018ifaconline,
abstract = {{\textcopyright} 2018 Several techniques have been proposed for piece-wise regression as extension to standard polynomial data fitting, either selecting the joints a priori or adding computational load for optimal joints. The pwpfit1 toolbox provides piece-wise polynomial fitting without pre-selection of joints using linear-least square (LSQ) optimization only. Additional constraints are realised as constraint matrices for the LSQ problem. We give an application example for the multi-variable aerodynamic coefficients of the general transport model in pre-stall and post-stall.},
added-at = {2023-01-10T09:19:16.000+0100},
author = {Cunis, Torbjørn},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/226b34363dc5d94f31696a265aff0deb1/tcunis},
doi = {10.1016/j.ifacol.2018.09.204},
file = {:Users/cunis/Documents/tex/Final/cunis2018_SYSID0024.pdf:pdf},
interhash = {9437a6335dae8d6ba3304e8f0523ea0c},
intrahash = {26b34363dc5d94f31696a265aff0deb1},
issn = {24058963},
journal = {IFAC-PapersOnLine},
keywords = {Aerospace Hybrid-System Identifcation,Grey-Box Identifcation,Multivariable Identifcation,Nonlinear Mechanical Modeling Toolboxes myown},
number = 15,
pages = {682--687},
timestamp = {2025-04-22T10:15:45.000+0200},
title = {The pwpfit Toolbox for Polynomial and Piece-wise Polynomial Data Fitting},
volume = 51,
year = 2018
}