Dissertation/Thesis Abstract

Model predictive control for adaptive digital human modeling
by Sheth, Katha Janak, M.S., The University of Iowa, 2010, 73; 1488280
Abstract (Summary)

We consider a new approach to digital human simulation, using Model Predictive Control (MPC). This approach permits a virtual human to react online to unanticipated disturbances that occur in the course of performing a task. In particular, we predict the motion of a virtual human in response to two different types of real world disturbances: impulsive and sustained. This stands in contrast to prior approaches where all such disturbances need to be known a priori and the optimal reactions must be computed off line. We validate this approach using a planar 3 degrees of freedom serial chain mechanism to imitate the human upper limb. The response of the virtual human upper limb to various inputs and external disturbances is determined by solving the Equations of Motion (EOM). The control input is determined by the MPC Controller using only the current and the desired states of the system. MPC replaces the closed loop optimization problem with an open loop optimization allowing the ease of implementation of control law. Results presented in this thesis show that the proposed controller can produce physically realistic adaptive simulations of a planar upper limb of digital human in presence of impulsive and sustained disturbances.

Indexing (document details)
Advisor: Abdel-Malek, Karim, Dasgupta, Soura, Bhatt, Rajankumar
Commitee: Arora, Jasbir, Bhatt, Rajankumar, Dasgupta, Soura, Grosland, Nicole M.
School: The University of Iowa
Department: Biomedical Engineering
School Location: United States -- Iowa
Source: MAI 49/03M, Masters Abstracts International
Subjects: Biomedical engineering, Electrical engineering, Mechanical engineering
Keywords: Digital human simulation, Disturbance response, Model predictive control, Motion prediction, Optimization, Upper limb model
Publication Number: 1488280
ISBN: 978-1-124-44235-8
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