Paper Info
Title
Identification And Control Of Electro-Mechanical Systems Using State-Dependent Parameter Estimation
Abstract
This paper addresses the important topic of electro-mechanical systems identification with an application in robotics. The standard inverse dynamic identification model with least squares (IDIM-LS) method of identifying models for robotic systems is based on the use of a continuous-time inverse dynamic model whose parameters are identified from experimental data by linear LS estimation. The paper describes a new alternative but related approach that exploits the state-dependent parameter (SDP) method of nonlinear model estimation and compares its performance with that of IDIM-LS. The SDP method is a two-stage identification procedure able to identify the presence and graphical shape of nonlinearities in dynamic system models with a minimum of a priori assumptions. The performance of the SDP method is evaluated on two electro-mechanical systems: the electro-mechanical positioning system and the second link of the TX40 robot. The experimental results demonstrate how SDP identification helps to avoid over-reliance on prior conceptions about the nature of the nonlinear characteristics and correct any deficiencies in this regard. Finally, a simulation study shows how the resulting SDP model is able to facilitate nonlinear control system design using linear-like design procedures.
Year
DOI
Venue
2017
10.1080/00207179.2016.1209565
INTERNATIONAL JOURNAL OF CONTROL
Keywords
Field
DocType
Robotics, state-dependent parameters, identification
Least squares,Inverse,Mathematical optimization,Control theory,A priori and a posteriori,Artificial intelligence,Estimation theory,Robot,Mechanical system,Robotics,Mathematics,Positioning system
Journal
Volume
Issue
ISSN
90
4
0020-7179
Citations 
PageRank 
References 
6
0.61
5
Authors
3
Name
Order
Citations
PageRank
Alexandre Janot18612.37
Peter C. Young2222110.94
Maxime Gautier347776.28