Stochastic parameter identification and control for LQR feedback control in robot periodic motion

For high-precision and high-speed control of robots, control systems are needed to be designed based on their dynamics models. The dynamics model requires identification of the dynamics parameters. However, due to un-modeled dynamics and noises, the conventional parameter identification methods such...

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Main Authors: Kazuki WATANABE, Masafumi OKADA
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2024-12-01
Series:Nihon Kikai Gakkai ronbunshu
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Online Access:https://www.jstage.jst.go.jp/article/transjsme/90/940/90_24-00171/_pdf/-char/en
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author Kazuki WATANABE
Masafumi OKADA
author_facet Kazuki WATANABE
Masafumi OKADA
author_sort Kazuki WATANABE
collection DOAJ
description For high-precision and high-speed control of robots, control systems are needed to be designed based on their dynamics models. The dynamics model requires identification of the dynamics parameters. However, due to un-modeled dynamics and noises, the conventional parameter identification methods such as LS (least square) method obtain only approximations whose optimality strongly depends on the control objectives. This paper proposes a method to identify values of the dynamics parameters suitable for use in control system design. In this method, the dynamics parameters are considered to be stochastic variables, and identified so that their variance is made small for large influence on control performance shaping its covariance to follow the desired one. By considering feedforward and feedback control system design with Linear quadratic regulator, the desired covariance matrix is introduced. Experiments using a planar 3-link manipulator show that the proposed method identifies the appropriate parameters, and the designed controller achieves highly accurate positioning of the end-effector.
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issn 2187-9761
language Japanese
publishDate 2024-12-01
publisher The Japan Society of Mechanical Engineers
record_format Article
series Nihon Kikai Gakkai ronbunshu
spelling doaj-art-b4a269231ea04c1aa31cd32c1c7ae97d2025-08-20T02:43:38ZjpnThe Japan Society of Mechanical EngineersNihon Kikai Gakkai ronbunshu2187-97612024-12-019094024-0017124-0017110.1299/transjsme.24-00171transjsmeStochastic parameter identification and control for LQR feedback control in robot periodic motionKazuki WATANABE0Masafumi OKADA1Department of Mechanical Engineering, Tokyo Institute of TechnologyDepartment of Mechanical Engineering, Tokyo Institute of TechnologyFor high-precision and high-speed control of robots, control systems are needed to be designed based on their dynamics models. The dynamics model requires identification of the dynamics parameters. However, due to un-modeled dynamics and noises, the conventional parameter identification methods such as LS (least square) method obtain only approximations whose optimality strongly depends on the control objectives. This paper proposes a method to identify values of the dynamics parameters suitable for use in control system design. In this method, the dynamics parameters are considered to be stochastic variables, and identified so that their variance is made small for large influence on control performance shaping its covariance to follow the desired one. By considering feedforward and feedback control system design with Linear quadratic regulator, the desired covariance matrix is introduced. Experiments using a planar 3-link manipulator show that the proposed method identifies the appropriate parameters, and the designed controller achieves highly accurate positioning of the end-effector.https://www.jstage.jst.go.jp/article/transjsme/90/940/90_24-00171/_pdf/-char/enparameter identificationminimum set of dynamics parametersfeedforward controlfeedback controllinear quadratic regulator
spellingShingle Kazuki WATANABE
Masafumi OKADA
Stochastic parameter identification and control for LQR feedback control in robot periodic motion
Nihon Kikai Gakkai ronbunshu
parameter identification
minimum set of dynamics parameters
feedforward control
feedback control
linear quadratic regulator
title Stochastic parameter identification and control for LQR feedback control in robot periodic motion
title_full Stochastic parameter identification and control for LQR feedback control in robot periodic motion
title_fullStr Stochastic parameter identification and control for LQR feedback control in robot periodic motion
title_full_unstemmed Stochastic parameter identification and control for LQR feedback control in robot periodic motion
title_short Stochastic parameter identification and control for LQR feedback control in robot periodic motion
title_sort stochastic parameter identification and control for lqr feedback control in robot periodic motion
topic parameter identification
minimum set of dynamics parameters
feedforward control
feedback control
linear quadratic regulator
url https://www.jstage.jst.go.jp/article/transjsme/90/940/90_24-00171/_pdf/-char/en
work_keys_str_mv AT kazukiwatanabe stochasticparameteridentificationandcontrolforlqrfeedbackcontrolinrobotperiodicmotion
AT masafumiokada stochasticparameteridentificationandcontrolforlqrfeedbackcontrolinrobotperiodicmotion