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State-dependent parameter model identification for inverse dead-zone control of a hydraulic manipulator

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State-dependent parameter model identification for inverse dead-zone control of a hydraulic manipulator. / West, Craig; Wilson, Emma Denise; Clairon, Q.; Monk, Stephen David; Montazeri, Allahyar; Taylor, C. James.

In: IFAC-PapersOnLine, Vol. 51, No. 15, 2018, p. 126-131.

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@article{dd3e342a75794f339a6d33bb432439f6,
title = "State-dependent parameter model identification for inverse dead-zone control of a hydraulic manipulator",
abstract = "The robotic platform in this study has dual, seven-function, hydraulically actuated manipulators, which are being used for research into assisted tele-operation for common nuclear decommissioning tasks, such as pipe cutting. The article concerns the identification of state-dependent parameter (SDP) models for joint angle control. Compared to earlier SDP analysis of the same device, the present work proposes a new way of representing the state-dependent gain and parametrises this using novel regret-regression methods. A mechanistic interpretation of this model yields dead-zone and angular velocity saturation coefficients, and facilitates SDP-based control with an inverse dead-zone. This approach integrates the input signal calibration, system identification and nonlinear control system design steps, using a relatively small data-set, allowing for straightforward recalibration when the dynamic characteristics have changed due to age and use, or after the installation of replacement parts.",
keywords = "Identification for control, nonlinear system identification, parameter-varying systems, robotic manipulators, anti-windup, application of nonlinear analysis and design",
author = "Craig West and Wilson, {Emma Denise} and Q. Clairon and Monk, {Stephen David} and Allahyar Montazeri and Taylor, {C. James}",
year = "2018",
doi = "10.1016/j.ifacol.2018.09.102",
language = "English",
volume = "51",
pages = "126--131",
journal = "IFAC-PapersOnLine",
issn = "2405-8963",
publisher = "IFAC Secretariat",
number = "15",

}

RIS

TY - JOUR

T1 - State-dependent parameter model identification for inverse dead-zone control of a hydraulic manipulator

AU - West, Craig

AU - Wilson, Emma Denise

AU - Clairon, Q.

AU - Monk, Stephen David

AU - Montazeri, Allahyar

AU - Taylor, C. James

PY - 2018

Y1 - 2018

N2 - The robotic platform in this study has dual, seven-function, hydraulically actuated manipulators, which are being used for research into assisted tele-operation for common nuclear decommissioning tasks, such as pipe cutting. The article concerns the identification of state-dependent parameter (SDP) models for joint angle control. Compared to earlier SDP analysis of the same device, the present work proposes a new way of representing the state-dependent gain and parametrises this using novel regret-regression methods. A mechanistic interpretation of this model yields dead-zone and angular velocity saturation coefficients, and facilitates SDP-based control with an inverse dead-zone. This approach integrates the input signal calibration, system identification and nonlinear control system design steps, using a relatively small data-set, allowing for straightforward recalibration when the dynamic characteristics have changed due to age and use, or after the installation of replacement parts.

AB - The robotic platform in this study has dual, seven-function, hydraulically actuated manipulators, which are being used for research into assisted tele-operation for common nuclear decommissioning tasks, such as pipe cutting. The article concerns the identification of state-dependent parameter (SDP) models for joint angle control. Compared to earlier SDP analysis of the same device, the present work proposes a new way of representing the state-dependent gain and parametrises this using novel regret-regression methods. A mechanistic interpretation of this model yields dead-zone and angular velocity saturation coefficients, and facilitates SDP-based control with an inverse dead-zone. This approach integrates the input signal calibration, system identification and nonlinear control system design steps, using a relatively small data-set, allowing for straightforward recalibration when the dynamic characteristics have changed due to age and use, or after the installation of replacement parts.

KW - Identification for control

KW - nonlinear system identification

KW - parameter-varying systems

KW - robotic manipulators

KW - anti-windup

KW - application of nonlinear analysis and design

U2 - 10.1016/j.ifacol.2018.09.102

DO - 10.1016/j.ifacol.2018.09.102

M3 - Journal article

VL - 51

SP - 126

EP - 131

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

SN - 2405-8963

IS - 15

ER -