Identification of a Robotic Arm Using Optimization Methods for Model Estimation 2002-01-2047
The system identification procedure is a powerful and flexible tool for the modeling of dynamic systems. This paper implements the theory of parametric identification in order to estimate a valid model of a flexible robotic arm. For this purpose experimental data is used for the estimation of ARMAX SISO models. A two-stages identification procedure (non-parametric & parametric) provides an insight about the system under identification. In the first stage, known signal analysis methods are applied (correlation-spectral analysis) for the estimation of frequencies and frequency response, and in the second stage, the estimation of ARMAX models is performed in order to fit a transfer function model to collected input-output data set. For the estimation of model's coefficients, use of Evolutionary Algorithms is implemented.
Citation: Kanarachos, A., Koulocheris, D., Dertimanis, V., and Vrazopoulos, H., "Identification of a Robotic Arm Using Optimization Methods for Model Estimation," SAE Technical Paper 2002-01-2047, 2002, https://doi.org/10.4271/2002-01-2047. Download Citation
Author(s):
A. Kanarachos, D. Koulocheris, V. Dertimanis, H. Vrazopoulos
Affiliated:
National Technical University of Athens
Pages: 7
Event:
International Body Engineering Conference & Exhibition and Automotive & Transportation Technology Congress
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Simulation and modeling
Mathematical models
Identification
Optimization
Robotics
Tools and equipment
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