Title
Identification of Physical Parameters and Instrumental Variables Validation With Two-Stage Least Squares Estimator
Abstract
This paper addresses physical parameters identification of mathematical models that are linear in relation to these physical parameters. We can obtain good results with the least squares technique, provided that a well-tuned data filtering is used, and by using instrumental variable (IV) methods, which deal with the problem of noisy observation matrix. However, IV theory is based on instruments validity. In econometrics, statistical tests evaluating instruments quality have been developed. They make use of the two-stage least squares estimator and the concentration parameter introduced by Basmann. In this paper we show how to extend econometric theory to control engineering. An algorithm evaluating instruments quality is presented and experimentally validated on a two-degrees-of-freedom SCARA robot.
Year
DOI
Venue
2013
10.1109/TCST.2012.2199321
Control Systems Technology, IEEE Transactions
Keywords
Field
DocType
least squares approximations,matrix algebra,parameter estimation,robots,statistical testing,IV method,SCARA robot,concentration parameter,control engineering,data filtering,econometrics,instrumental variable validation,least squares technique,observation matrix,physical parameter identification,statistical test,two-stage least squares estimator,Experimental identification,instrumental variables (IVs) evaluation,two-stage least squares (LS) estimator
Least squares,Mathematical optimization,Newey–West estimator,Control theory,Algorithm,Generalized least squares,Non-linear least squares,Total least squares,Explained sum of squares,Simultaneous equations model,Linear least squares,Mathematics
Journal
Volume
Issue
ISSN
21
4
1063-6536
Citations 
PageRank 
References 
4
0.52
3
Authors
3
Name
Order
Citations
PageRank
Alexandre Janot18612.37
Pierre-olivier Vandanjon2485.38
Maxime Gautier347776.28