Thesis(M.S.)--Auburn University, 2006. / Abstract. Vita. Includes bibliographic references.

Thesis (M.S.)--Washington State University, December 2006. / Includes bibliographical references (p. 55-57).

Thesis (Ph. D.)--City University of Hong Kong, 2005. / "Submitted to Department of Electronic Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves 109-118).

University of Macau / Faculty of Science and Technology / Department of Electrical and Computer Engineering

Thesis (Ph. D.)--University of Missouri-Columbia, 2007. / The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on January 31, 2008) Vita. Includes bibliographical references.

Thesis (Ph. D.)--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 84-89).

This thesis proposes a technique to determine and improve the performance of a sensorless speed estimator for an induction motor based on Motor Current Signature Analysis (MCSA). The theoretical concepts underlying the parameter based observer are developed first and then the model of the observer is built using Simulink. The observer is developed based on Model Reference Adaptive System (MRAS). The dynamic performance of the observer and its behavior due to variation of machine parameters is studied. The error in speed estimated using this observer is shown and the ability of MCSA to retune the rotor speed from the stator current spectrum. The spectrum estimation technique has been implemented using a software routine in Matlab. Both the observer and MCSA techniques were implemented practically on an induction motor. The performance of the combined sensorless speed estimation system was tested and verified.

The thesis presents the development of force controller to maintain desired normal forces during a very stiff contact operation conducted in a Computer Numerical Control (CNC) machine. Force controller approach described in this thesis requires the accurate knowledge of the nominal tool path a priori. Obtaining the nominal tool path accurately is carried out by a vision based profile tracking system presented in this thesis. Both the force control and visual profile tracking systems require the development of an active control system to respond to force and vision signals. To facilitate the active control, a two-stage approach has been taken. The first stage is to bring the CNC machine under real-time control of an external computer. The second stage is the design of the active axis controller. This is achieved by adding sensor feedback loops to the external axis controller. The purpose of the active vision based profile tracking system is to automatically generate the tool path accurately. Emphasis is on combining low resolution vision with visual control of the precision CNC machine to attain the accuracy required for metal spinning. Combination of visual profile tracking and an edge detection method that gives sub-pixel accuracy were used to obtain the required tool path. A curvature detection algorithm was developed to identify segments of the tool path by assuming that the tool path consists of circular and straight line segments. The developed active force controller operates in a dynamic setup and is used to maintain tool forces at desired levels. The complete control system operates in a manner similar to reaction compensation and the force controller can be viewed as an integrating on-off controller with minimum integral wind-up effect. As a result, a direct dependency of the control efforts on error signals has been eliminated. In addition, the force controller brings in artificial damping that ensures the stability of the control system. To demonstrate the effect of the force controller, spun component qualities were assessed.

The thesis presents the development of force controller to maintain desired normal forces during a very stiff contact operation conducted in a Computer Numerical Control (CNC) machine. Force controller approach described in this thesis requires the accurate knowledge of the nominal tool path a priori. Obtaining the nominal tool path accurately is carried out by a vision based profile tracking system presented in this thesis. Both the force control and visual profile tracking systems require the development of an active control system to respond to force and vision signals. To facilitate the active control, a two-stage approach has been taken. The first stage is to bring the CNC machine under real-time control of an external computer. The second stage is the design of the active axis controller. This is achieved by adding sensor feedback loops to the external axis controller. The purpose of the active vision based profile tracking system is to automatically generate the tool path accurately. Emphasis is on combining low resolution vision with visual control of the precision CNC machine to attain the accuracy required for metal spinning. Combination of visual profile tracking and an edge detection method that gives sub-pixel accuracy were used to obtain the required tool path. A curvature detection algorithm was developed to identify segments of the tool path by assuming that the tool path consists of circular and straight line segments. The developed active force controller operates in a dynamic setup and is used to maintain tool forces at desired levels. The complete control system operates in a manner similar to reaction compensation and the force controller can be viewed as an integrating on-off controller with minimum integral wind-up effect. As a result, a direct dependency of the control efforts on error signals has been eliminated. In addition, the force controller brings in artificial damping that ensures the stability of the control system. To demonstrate the effect of the force controller, spun component qualities were assessed.

Thesis (M.S.)--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references (ℓ. 50-51)