Development and feasibility of economical hardware and software in control theory application

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dc.contributor.author Black, Derek J.
dc.date.accessioned 2017-11-01T15:14:12Z
dc.date.available 2017-11-01T15:14:12Z
dc.date.issued 2017-12-01 en_US
dc.identifier.uri http://hdl.handle.net/2097/38170
dc.description.abstract Control theory is the study of feedback systems, and a methodology investigated by many engineering students throughout most universities. Because of control theory's broad and interdisciplinary nature, it necessitates further study by application through experimental learning and laboratory practice. Typically, the hardware used to connect the theoretical aspects of controls to the practical can be expensive, big, and time consuming to the students and instructors teaching on the equipment. Alternatively, using cheaper sensors and hardware, such as encoders and motor drivers, can obfuscate the collected data in a way that creates a disconnect between developed theoretical models and actual system results. This disconnect can dissuade the idea that systems can and will follow a modeled behavior. This thesis attempts to assess the feasibility of a piece of laboratory apparatus named the NERMLAB. Multiple experiments will be conducted on the NERMLAB system and compared against time-tested hardware to demonstrate the practicality of the NERMLAB system in control theory application. en_US
dc.language.iso en_US en_US
dc.publisher Kansas State University en
dc.subject Control Theory en_US
dc.subject Software en_US
dc.subject Higher Education en_US
dc.subject Motor control en_US
dc.subject System Identification en_US
dc.subject Mathematical modeling en_US
dc.title Development and feasibility of economical hardware and software in control theory application en_US
dc.type Thesis en_US
dc.description.degree Master of Science en_US
dc.description.level Masters en_US
dc.description.department Department of Mechanical and Nuclear Engineering en_US
dc.description.advisor Dale E. Schinstock en_US
dc.date.published 2017 en_US
dc.date.graduationmonth December en_US


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