Adaptive Motion Estimation and Control of Intelligent Walkers
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Date
2015-07-10
Authors
Zengin, Nursefa
Journal Title
Journal ISSN
Volume Title
Publisher
University of Waterloo
Abstract
One of the most critical factors in the quality of elderly lives is their ability to move. As
the size of the ageing society grows, more elderly people suffer from walking impairments.
Most of them prefer to stay at home due to the shortage of the nursing care staff, since
they deal with the daily challenges alone. Robotics researchers have developed various
intelligent walking support systems to meet the needs of elderly and handicapped people.
A particular problem in path tracking for such systems is maintaining the tracking performance,
which is affected by the center of gravity (CG) shifts and load changes due to
human-walker interactions. This thesis focuses on design of feedback controllers for safe
motion of intelligent walker (i-walker) systems robust to CG shifts and load changes. Our
design follows a two level approach, one for kinematics, the other for dynamics. The high
level kinematic controller is designed based on integrator backstepping to produce desired
velocities required for trajectory tracking. The low level dynamic controller is composed of
a feedback linearization unit and a linear feedback controller to apply the control torque
for tracking the desired velocity produced by the high level kinematic controller. As dynamic
controllers, proportional-derivative (PD) and sliding mode controllers (SMCs) are
designed. In our initial design, we assume that all system states are available. However, in
the actual case, even if the wheel velocities can be measured with some sensor devices like
tachometers, the measurements carry noise, which poses important problems in control algorithms.
To obtain the estimates of the wheel velocities, avoiding the noise problems, the
design of sliding mode observers and high gain observers is studied. The state feedback
PD and SMC schemes are later integrated with these observers to form implementable
output feedback controllers. In practice, the human mass and the distance due to the CG
shift depend on the user. To address this issue, the output feedback control designs are
further made adaptive, integrating with a parameter identifier to estimate these variables.
The parameter identifier design involves a linear parametric model of the i-walker system
dynamics and a least-square adaptive law based on this parametric model. Adaptive versions
of the above observers and control designs are done utilizing estimated parameters
and states. The effectiveness and applicability of the proposed controllers are verified via
various simulations in MATLAB/Simulink environment.
Description
Keywords
Intelligent walker, nonlinear control, observer, robust control, parameter estimation, state estimation