Many applications such as automobiles, gyroscopes, machine tools, and transfer systems require orientation control of a rotating shaft. Demands for multi-degree of freedom (DOF) actuators in modern industries have motivated this research to develop a ball-joint-like, brushless, direct-drive spherical wheel motor (SWM) that offers a means to control the orientation of its rotating shaft.
This thesis presents a general method for deriving a closed-form magnetic field solution for precise torque calculation. The method, referred here as distributed multi pole (DMP) modeling, inherits many advantages of the dipole model originally conceptualized in the context of physics, but provides an effective means to account for the shape and magnetization of the physical magnet. The DMP modeling method has been validated by comparing simulated fields and calculated forces against data obtained experimentally and numerically; the comparisons show excellent agreement. The DMP models provide a basis to develop a non-contact magnetic sensor for orientation sensing and control of a rotating shaft. Three controllers have been designed and experimentally implemented for the SWM; open-loop and PD with/without an observer. The OL control system, which decouples the spin from the shaft inclination, provides the fundamental design structure for the SWM and serves as a basis for designing feedback controllers with/without an observer.
While the observer and controller designs have been developed in the context of a spherical wheel motor, these techniques along with the models and analysis tools developed in this research can be applied to design, analysis and control of most electromagnetic devices. We expect that the analytical method along with the orientation sensor and spherical wheel motor will have broad spectrum of applications.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/26616 |
| Date | 14 November 2007 |
| Creators | Son, Hungsun |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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