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Model Parameter Identification of Nonlinear Dynamics Systems by Trajectory Pattern Method

[+] Author Affiliations
Jahangir Rastegar, Dake Feng, Kavous Jorabchi

State University of New York at Stony Brook, Stony Brook, NY

Paper No. DETC2010-28254, pp. 1499-1507; 9 pages
  • ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 34th Annual Mechanisms and Robotics Conference, Parts A and B
  • Montreal, Quebec, Canada, August 15–18, 2010
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4410-6 | eISBN: 978-0-7918-3881-5
  • Copyright © 2010 by ASME


In this paper, a new method is presented for model parameter identification of a large class of fully controlled nonlinear dynamics systems such as robot manipulators. The method uses trajectory patterns with feed-forward controls to identify model parameters of the system. The developed method ensures full system stability, does not require close initial estimated values for the parameters to be identified, and provides a systematic method of emphasizing on the estimation of the parameters associated with lower order terms of the system dynamics model and gradually upgrading the accuracy with which the model parameters, particularly those associated with the higher order terms of the system dynamics model are estimated. The developed method is based on Trajectory Pattern Method (TPM). In this method, for a pattern of motion the inverse dynamics model of the system is derived in algebraic form in terms of the trajectory pattern parameters. The system dynamics model parameters are then identified using a systematic algorithm which ensures system stability as well as accurate estimation of the model parameters associated with lower as well as higher order terms. Mathematical proof of convergence of the developed method and an example of its application are provided.

Copyright © 2010 by ASME



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