An instrumental variable method for robot identification based on time variable parameter estimation

Title:

An instrumental variable method for robot identification based on time variable parameter estimation

Creator:

Brunot, Mathieu, Janot, Alexandre, Young, Peter C., and Carrillo, Francisco

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:1d5de55c-2d00-4752-a544-382abc73219f
uuid:1d5de55c-2d00-4752-a544-382abc73219f
doi:10.14736/kyb-2018-1-0202

Subject:

industrial robot system, system identification, instrumental variable method, parameter estimation, Kalman filter, and fixed interval smoothing

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Kybernetika | 2018 Volume:54 | Number:1

Harvested from:

CDK

Metadata only:

false