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Grasped Object Detection for Adaptive Control of a Prosthetic Hand

Andrecioli, Ricardo
http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779

Abstract Details

2013, Master of Science, University of Akron, Mechanical Engineering.
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.
Erik Engeberg, Dr. (Advisor)
Subramaniya Hariharan, Dr. (Committee Member)
Jiang Zhe, Dr. (Committee Member)
151 p.
Biomechanics; Mechanical Engineering
Powered upper limb prosthesis; adaptive control; nonlinear control; robust control; stiffness control; stiffness detection.

Recommended Citations

Citations

  • Andrecioli, R. (2013). Grasped Object Detection for Adaptive Control of a Prosthetic Hand [Master's thesis, University of Akron]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779

    APA Style (7th edition)

  • Andrecioli, Ricardo. Grasped Object Detection for Adaptive Control of a Prosthetic Hand. 2013. University of Akron, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779.

    MLA Style (8th edition)

  • Andrecioli, Ricardo. "Grasped Object Detection for Adaptive Control of a Prosthetic Hand." Master's thesis, University of Akron, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=akron1364481779

    Chicago Manual of Style (17th edition)

akron1364481779
770
© 2013, some rights reserved.Creative Commons License Grasped Object Detection for Adaptive Control of a Prosthetic Hand by Ricardo Andrecioli is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Akron and OhioLINK.