Grasped Object Detection for Adaptive Control of a Prosthetic Hand

Bibliographic Details
Main Author:	Andrecioli, Ricardo
Language:	English
Published:	University of Akron / OhioLINK 2013
Subjects:	Biomechanics Mechanical Engineering Powered upper limb prosthesis adaptive control nonlinear control robust control stiffness control stiffness detection.
Online Access:	http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779

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spelling	ndltd-OhioLink-oai-etd.ohiolink.edu-akron13644817792021-08-03T05:21:28Z Grasped Object Detection for Adaptive Control of a Prosthetic Hand Andrecioli, Ricardo Biomechanics Mechanical Engineering Powered upper limb prosthesis adaptive control nonlinear control robust control stiffness control stiffness detection. Unfortunately, statistical analyses of amputee data shows an increase of the population with upper limb losses either by trauma or birth congenital defects. Several prosthesis options are commercially available, including electric powered prostheses. A review of surveys for upper limb prosthesis users have indicated improvement opportunities in the prosthesis design as well as improved functionality and controls. After review of literature, a PID sliding mode position controller and an adaptive PID sliding mode controller are presented for a prosthetic hand. The adaptive controller smoothly modulates the gains based on the detected stiffness of the grasped object. Three main control strategies will be compared: PID force control, sliding mode position and hybrid sliding mode force-position controllers. For each control option, an adaptive version will also be tested via benchtop experiments. In order to evaluate the performance of each controller under several grasping circumstances, a special manipulandum was designed to provide variable linear and nonlinear stiffness behavior, then each controller was then evaluated according to an experiment plan. The results from benchtop experiments indicate statistically significant improvements such as improved tracking response and reduced steady state error in the system response when using the adaptive controller for all three control cases considered. When comparing Force versus Position versus Hybrid Force-Position control, the latter when equipped of the adaptation method has presented the best results.Preliminary amputee experiments were also conducted using the adaptive hybrid force-position controller in comparison to the constant gain controller as well as the amputees’ current prostheses for daily use. The results of these experiments show that the adaptive hybrid force-position sliding mode controller enabled the amputees to smoothly handle the manipulandum without breaking it. 2013-06-06 English text University of Akron / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779 http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779 unrestricted This thesis or dissertation is protected by copyright: some rights reserved. It is licensed for use under a Creative Commons license. Specific terms and permissions are available from this document's record in the OhioLINK ETD Center.
collection	NDLTD
language	English
sources	NDLTD
topic	Biomechanics Mechanical Engineering Powered upper limb prosthesis adaptive control nonlinear control robust control stiffness control stiffness detection.
spellingShingle	Biomechanics Mechanical Engineering Powered upper limb prosthesis adaptive control nonlinear control robust control stiffness control stiffness detection. Andrecioli, Ricardo Grasped Object Detection for Adaptive Control of a Prosthetic Hand
author	Andrecioli, Ricardo
author_facet	Andrecioli, Ricardo
author_sort	Andrecioli, Ricardo
title	Grasped Object Detection for Adaptive Control of a Prosthetic Hand
title_short	Grasped Object Detection for Adaptive Control of a Prosthetic Hand
title_full	Grasped Object Detection for Adaptive Control of a Prosthetic Hand
title_fullStr	Grasped Object Detection for Adaptive Control of a Prosthetic Hand
title_full_unstemmed	Grasped Object Detection for Adaptive Control of a Prosthetic Hand
title_sort	grasped object detection for adaptive control of a prosthetic hand
publisher	University of Akron / OhioLINK
publishDate	2013
url	http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779
work_keys_str_mv	AT andrecioliricardo graspedobjectdetectionforadaptivecontrolofaprosthetichand
_version_	1719418522954629120

Grasped Object Detection for Adaptive Control of a Prosthetic Hand

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