An Instrumental Variable Method for Robot Identification Based on Time Variable Parameter
Date
2018
Authors
Brunot, Mathieu
Janot, Alexandre
Young, Peter
Carrillo, Francisco
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The Academy of Sciences of the Czech Republic
Abstract
This paper considers the data-based identification of industrial robots using an instrumental variable method that uses off-line estimation of the joint velocities and acceleration signals based only on the measurement of the joint positions. The usual approach to this problem relies on a `tailor-made' prefiltering procedure for estimating the derivatives that depends on good prior knowledge of the system's bandwidth. The paper describes an alternative Integrated Random Walk SMoothing (IRWSM) method that is more robust to deficiencies in such a priori knowledge and exploits an optimal recursive algorithm based on a simple integrated random walk model and a Kalman filter with associated fixed interval smoothing. The resultant IDIM-IV instrumental variable method, using this approach to signal generation, is evaluated by its application to an industrial robot arm and comparison with previously proposed methods.
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Kybernetika
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Journal article
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2037-12-31
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