Optimal Design of a Passively-Controlled Gyro for Balance Assistance

Master thesis (2020)

Authors

R.M. Helwig Mechanical Engineering

Contributors

H. Vallery Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (supervisor 1)
Andrew Berry Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (supervisor 2)
B.T. Sterke Support Biomechanical Engineering (supervisor 2)
D.S. Lemus Perez Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering (supervisor 2)
A. Sakes Medical Instruments & Bio-Inspired Technology - Mechanical, Maritime and Materials Engineering (supervisor 2)
Faculty
Mechanical Engineering
Copyright: © 2020 Roemer Helwig
Optimal design Control moment gyro Impedance optimization Balance assistance
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Published Date

28-02-2020

Language

English

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Faculty

Mechanical Engineering

Abstract

Falling is a significant problem for older adults. It can cause severe injury and even death. Furthermore, the fear of falling has a significant influence on the life of the elderly, and therefore they reduce their physical activity. Two new balance assistive devices are being developed to reduce the risk of falling. Both devices use a control moment gyroscope (CMG) to generate a moment to counter the falling motion. One device consists of a single CMG. The other device consists of two CMGs that are coupled such that the gimbals rotate in opposite direction. This is called a scissored pair CMG (SPCMG). The purpose of this study was to examine whether it is possible to design an (SP)CMG with a passive mechanism that exploits gyroscopic precession of gimbal(s) to emulate different types of impedances for balance assistance. To examine this, first, the equations of motion of a CMG and an SPCMG were derived. Next, the equations of motion were used to derive the impedance of the system. The impedance was optimized such that it would simulate the behaviour of a spring, a damper, a mass, a mass-spring-damper system, and a rotational PD controller which is proportional to the XCoM (PDXCoM), a measure of stability. The optimization used a gradient-based algorithm to find the minimum. Multiple optimizations with different random initial guesses were performed to increase the chance to find the global minimum. Two sets of optimizations were performed.
One optimization with and one optimization without bounds on the optimization. The sets parameters that led to the best fit were used in a walking simulation to calculate the moments the device would generate during normal walking. It is shown that it is possible to simulate the dynamics of a spring, a damper, a mass, and a mass-springdamper system with a CMG and an SPCMG. However, it was not possible to replicate the dynamics of the PDXCoM with a CMG and an SPCMG. A walking simulation showed that the generated moments of the (SP)CMG were in the opposite direction of the angular velocity of the human. Therefore, using a passive mechanism to control an (SP)CMG could be used as balance assistance.