Thesis (Ph. D.)--University of Notre Dame, 2004. / Thesis directed by Steven B. Skaar for the Department of Aerospace and Mechanical Engineering. "March 2004." Includes bibliographical references (leaves 277-280).

Thesis (M.S.)--West Virginia University, 2002. / Title from document title page. Document formatted into pages; contains ix, 150 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 99).

Thesis (M.Eng.)--University of Louisville, 2009. / Title and description from thesis home page (viewed May 15, 2009). Department of Mechanical Engineering. Vita. "April 2009." Includes bibliographical references (p. 60-61).

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 121-123). Also available via the Internet.

Thesis (M.Eng.)--University of Louisville, 2008. / Title and description from thesis home page (viewed December 19, 2008). Department of Mechanical Engineering. Vita. "December 2008." Includes bibliographical references (p. 97-100).

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: legrest; wheelchair. Includes bibliographical references (leaves 106-107 ).

by Hon Nin Chow. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 79-84). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Organization of the Thesis --- p.3 / Chapter 2 --- Literature Survey --- p.6 / Chapter 2.1 --- Learning-by-Demonstration --- p.6 / Chapter 2.2 --- Neural Networks --- p.7 / Chapter 2.3 --- Navigation Learning --- p.8 / Chapter 2.4 --- Localization --- p.9 / Chapter 2.5 --- Robotic Wheelchair --- p.10 / Chapter 3 --- System Implementation --- p.12 / Chapter 3.1 --- Hardware Platform --- p.12 / Chapter 3.2 --- Software Platform --- p.14 / Chapter 3.3 --- Basic Functionality --- p.15 / Chapter 3.3.1 --- Collision Avoidance --- p.15 / Chapter 3.3.2 --- Wearable Eye-jaw Control Interface --- p.16 / Chapter 4 --- Learning Human Navigational Skill --- p.22 / Chapter 4.1 --- Introduction --- p.22 / Chapter 4.2 --- Problem Formulation --- p.23 / Chapter 4.3 --- Approach --- p.23 / Chapter 4.4 --- Experimental Study --- p.26 / Chapter 4.4.1 --- Settings --- p.26 / Chapter 4.4.2 --- Results --- p.30 / Chapter 4.5 --- Discussions --- p.31 / Chapter 5 --- Learning from Multi-phase Demonstrations --- p.33 / Chapter 5.1 --- Introduction --- p.33 / Chapter 5.2 --- Problem Formulation --- p.34 / Chapter 5.3 --- Approach --- p.35 / Chapter 5.4 --- Experimental Study --- p.35 / Chapter 5.4.1 --- Settings --- p.35 / Chapter 5.4.2 --- Results --- p.37 / Chapter 5.5 --- Evaluation of Learning Performance --- p.37 / Chapter 5.6 --- Discussions --- p.43 / Chapter 6 --- Localization Learning --- p.44 / Chapter 6.1 --- Introduction --- p.44 / Chapter 6.2 --- Problem Formulation --- p.45 / Chapter 6.3 --- Approach --- p.45 / Chapter 6.4 --- Experimental Study --- p.46 / Chapter 6.4.1 --- Settings --- p.46 / Chapter 6.4.2 --- Result 1: Localization Performance --- p.47 / Chapter 6.4.3 --- Result 2: Similar Sensor Patterns in Various Configurations . --- p.53 / Chapter 6.4.4 --- Result 3: Small Variations in Major Dimensions of Environ- mental Feature along the Route --- p.53 / Chapter 6.5 --- Discussions --- p.59 / Chapter 6.5.1 --- Accuracy --- p.59 / Chapter 6.5.2 --- Choices of Sensor-Configuration Mappings --- p.60 / Chapter 7 --- Conclusion --- p.62 / Chapter 7.1 --- Contributions --- p.62 / Chapter 7.2 --- Future Work --- p.65 / Chapter A --- Cascade Neural Network --- p.67 / Chapter B --- Trajectories for the Navigation Learning in Chapter 4 --- p.69 / Chapter C --- Publications Resulted from the Study --- p.78

Thesis (M Design)--University of South Australia, 1995

Thesis (M.S.)--Mechanical Engineering, Georgia Institute of Technology, 2007. / William Singhose, Committee Co-Chair ; Stephen Sprigle, Committee Co-Chair ; Harvey Lipkin, Committee Member.

M.Ing. (Electrical And Electronic) / Because of the high costs of available wheelchair drive systems, an investigation into an alternative drive system was undertaken. Three phase cage rotor induction machines were selected as the most suitable replacement for the current DC machines, having less maintenance requirements and costing less to manufacture. The 24V DCsupplied by the on board battery is converted to three phase alternating current with variable amplitude and frequency by means of a MOSFET inverter. A simple control algorithm, a differential algorithm and a PWM algorithm are pro.grammed into a INTEL 8097 micro regulator. The control algorithm ramps up the stator frequencies of the machines in a fixed time interval to a value determined by the operator. This results in a constant relation between the two frequencies, complying to the differential requirement. During an overcurrent situation, the control ramps the machine frequencies to a value which will tend to reduce the stator currents while still complying to the differential requirement. The airgap flux of the machines is kept constant by keeping the relation of the stator frequency to the stator voltage constant, except in the low speed area, where the stator voltage is altered to compensate for the voltage drop over the stator resistance. Because of the operator closing some sort of a speed feedback loop, no attempt was made to reduce the speed error of the drive caused by the slip-nature of induction machines. In order to test the drive under different operating conditions, a test setup was developed, employing DC machines connected mechanically to the traction machines.