Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Control on 11/07/2016, available online: http://www.tandfonline.com/doi/full/10.1080/00207179.2016.1209565
Accepted author manuscript, 610 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Identification and control of electro-mechanical systems using state-dependent parameter estimation
AU - Janot, Alexandre
AU - Young, Peter C.
AU - Gautier, Maxime
N1 - This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Control on 11/07/2016, available online: http://www.tandfonline.com/doi/full/10.1080/00207179.2016.1209565
PY - 2017/4
Y1 - 2017/4
N2 - This paper addresses the important topic of electromechanical systems identification with an application in robotics. The standard 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 Least Squares 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 electromechanical systems: the Electro-Mechanical Positioning System (EMPS) 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.
AB - This paper addresses the important topic of electromechanical systems identification with an application in robotics. The standard 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 Least Squares 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 electromechanical systems: the Electro-Mechanical Positioning System (EMPS) 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.
KW - Robotics
KW - State-Dependent-Parameters
KW - Identification
U2 - 10.1080/00207179.2016.1209565
DO - 10.1080/00207179.2016.1209565
M3 - Journal article
VL - 90
SP - 643
EP - 660
JO - International Journal of Control
JF - International Journal of Control
SN - 0020-7179
IS - 4
ER -