Date of Degree
MS (Master of Science)
First Committee Member
Second Committee Member
Nicole M Grosland
Third Committee Member
Fourth Committee Member
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.
Digital Human Simulation, Disturbance Response, Model Predictive Control, Motion Prediction, Optimization, Upper Limb Model
ix, 63 pages
Includes bibliographical references (pages 62-63).
Copyright 2010 Katha Janak Sheth
Sheth, Katha Janak. "Model predictive control for adaptive digital human modeling." MS (Master of Science) thesis, University of Iowa, 2010.