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dc.contributor.advisorHagan, Martin T.
dc.contributor.authorEvert, Jeremy Paul
dc.date.accessioned2014-04-17T20:08:27Z
dc.date.available2014-04-17T20:08:27Z
dc.date.issued2010-12-01
dc.identifier.urihttps://hdl.handle.net/11244/10199
dc.description.abstractThe smart sensor car is a test bed for demonstrating soft sensor concepts. The smart car follows the magnetic field coming from a wire track. Sensors on the smart car detect the magnetic field and generate signals. Those signals are conditioned and converted to digital numbers, which are used by the neural network as inputs. The neural network calculates the car position from these inputs. The car position is sent to a controller that calculates the car steering angle. The commands from the controller drive the smart sensor car around the track, where the sensors generate different signals resulting in different commands from the controller. The neural network is implemented on an Field Programmable Gate Array (FPGA) in a serial configuration.
dc.formatapplication/pdf
dc.languageen_US
dc.publisherOklahoma State University
dc.rightsCopyright is held by the author who has granted the Oklahoma State University Library the non-exclusive right to share this material in its institutional repository. Contact Digital Library Services at lib-dls@okstate.edu or 405-744-9161 for the permission policy on the use, reproduction or distribution of this material.
dc.titleTest Bed for Demonstrating and Teaching Soft Sensor Concepts
dc.typetext
dc.contributor.committeeMemberLatino, Carl D.
dc.contributor.committeeMemberStine, James E., Jr.
osu.filenameEvert_okstate_0664M_11180.pdf
osu.collegeEngineering, Architecture, and Technology
osu.accesstypeOpen Access
dc.description.departmentSchool of Electrical & Computer Engineering
dc.type.genreThesis
dc.subject.keywordsfpga
dc.subject.keywordsneural network
dc.subject.keywordssoft sensor


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