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Using Nonlinear Feedback Control to ...

Wagner, Edward V.

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Using Nonlinear Feedback Control to Model Human Landing Mechanics.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Using Nonlinear Feedback Control to Model Human Landing Mechanics./
作者:	Wagner, Edward V.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	199 p.
附註:	Source: Dissertation Abstracts International, Volume: 79-06(E), Section: B.
Contained By:	Dissertation Abstracts International79-06B(E).
標題:	Mechanical engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=11016072

Using Nonlinear Feedback Control to Model Human Landing Mechanics.
Wagner, Edward V.

Using Nonlinear Feedback Control to Model Human Landing Mechanics. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 199 p.

Source: Dissertation Abstracts International, Volume: 79-06(E), Section: B.

Thesis (Ph.D.)--University of Southern California, 2018.

Human beings interact with a variety of terrains on a regular basis, adapting their joint coordination strategies to account for these diverse mechanical conditions. Because these adaptive processes are always engaged, they play an integral role in driving the dynamics of the body. Attempts to model macroscale human body landing dynamics have, until recently, largely neglected this active aspect, focusing instead on describing the system in terms of mechanical elements with predefined parameters. Thus, the aim of this research is to develop and validate an experimentally based dynamic model of the human body that captures this ability to modulate ground reaction forces to achieve goal oriented task objectives. The goal of modeling, as Weyand puts it, is to "bridge the gap between overly simplistic models which provide little insight and overly complex models which are not broadly applicable." During foot-first landings human subjects attempt to satisfy multiple, sometimes competing, demands: impact preparation, total body vertical momentum reduction, and system stabilization. All of these objectives are subject to constraints imposed by the limits of the physical system: kinematic manifolds steering away from joint extension limits and kinetic upper bounds on the ground reaction forces to avoid overloading segments or over exerting joints. To characterize the motor control strategies by which humans accomplish these objectives, foot-first drop-landing experiments are conducted with human subjects. In the task a subject is asked to step off a platform and land on force plates embedded in the floor under three conditions: self-selected normal, harder-than-normal, and softer-than-normal. The position of retroreflective markers on each segment are tracked in the sagittal plane of motion using an ultrahigh-speed camera to ensure all kinematic impact phenomena are properly documented. Due to the bifurcation in dynamic conditions during landings with impact, a novel time-dependent filtering method is developed and implemented to provide second order time-derivatives of these kinematics across the different phases of landing. Subjects exhibit phase specific control strategies during landing including segment pull-up during the flight phase which reduces the downward velocity of their end effectors, stiffness regulation during impact phase modulating the peak vertical ground reaction force, and subject specific joint coordination manifolds during the post-impact phase. This research proposes a 2D experiment-based model, composed of 4 rigid links connected by hinge joints and driven by nonlinear feedback controlled net joint moment actuators is complex enough to capture the dynamics of the human body during multiphase drop-landing tasks involving foot-first impact, as measured by the vertical ground reaction forces. The phase-specific feedback control architecture changes according to the changing mechanical objectives of each phase of landing: joint angle following control during flight phase, impedance control during the impact phase, and energy-shaping control during the post-impact phase. Simulations revealed that the proposed model accurately (+/-10°) follows joint angles during the flight phase, accurately (+/-10%) predicts both the peak vertical ground reaction force and total vertical impulse during the impact phase, and sufficiently dissipates the remaining kinetic energy to stabilize the system during the post-impact phase of a drop landing for all three drop landing conditions.Subjects--Topical Terms:

649730
Mechanical engineering.

Using Nonlinear Feedback Control to Model Human Landing Mechanics.
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520 $a Human beings interact with a variety of terrains on a regular basis, adapting their joint coordination strategies to account for these diverse mechanical conditions. Because these adaptive processes are always engaged, they play an integral role in driving the dynamics of the body. Attempts to model macroscale human body landing dynamics have, until recently, largely neglected this active aspect, focusing instead on describing the system in terms of mechanical elements with predefined parameters. Thus, the aim of this research is to develop and validate an experimentally based dynamic model of the human body that captures this ability to modulate ground reaction forces to achieve goal oriented task objectives. The goal of modeling, as Weyand puts it, is to "bridge the gap between overly simplistic models which provide little insight and overly complex models which are not broadly applicable." During foot-first landings human subjects attempt to satisfy multiple, sometimes competing, demands: impact preparation, total body vertical momentum reduction, and system stabilization. All of these objectives are subject to constraints imposed by the limits of the physical system: kinematic manifolds steering away from joint extension limits and kinetic upper bounds on the ground reaction forces to avoid overloading segments or over exerting joints. To characterize the motor control strategies by which humans accomplish these objectives, foot-first drop-landing experiments are conducted with human subjects. In the task a subject is asked to step off a platform and land on force plates embedded in the floor under three conditions: self-selected normal, harder-than-normal, and softer-than-normal. The position of retroreflective markers on each segment are tracked in the sagittal plane of motion using an ultrahigh-speed camera to ensure all kinematic impact phenomena are properly documented. Due to the bifurcation in dynamic conditions during landings with impact, a novel time-dependent filtering method is developed and implemented to provide second order time-derivatives of these kinematics across the different phases of landing. Subjects exhibit phase specific control strategies during landing including segment pull-up during the flight phase which reduces the downward velocity of their end effectors, stiffness regulation during impact phase modulating the peak vertical ground reaction force, and subject specific joint coordination manifolds during the post-impact phase. This research proposes a 2D experiment-based model, composed of 4 rigid links connected by hinge joints and driven by nonlinear feedback controlled net joint moment actuators is complex enough to capture the dynamics of the human body during multiphase drop-landing tasks involving foot-first impact, as measured by the vertical ground reaction forces. The phase-specific feedback control architecture changes according to the changing mechanical objectives of each phase of landing: joint angle following control during flight phase, impedance control during the impact phase, and energy-shaping control during the post-impact phase. Simulations revealed that the proposed model accurately (+/-10°) follows joint angles during the flight phase, accurately (+/-10%) predicts both the peak vertical ground reaction force and total vertical impulse during the impact phase, and sufficiently dissipates the remaining kinetic energy to stabilize the system during the post-impact phase of a drop landing for all three drop landing conditions.
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