{"id":{"repo_id":"wayne-thes","oai_identifier":"oai:digitalcommons.wayne.edu:oa_dissertations-1971"},"canonical_url":"https://search.dev.ndltd.org/etd/wayne-thes/oai:digitalcommons.wayne.edu:oa_dissertations-1971","repository":{"repo_id":"wayne-thes","name":"Wayne State University","base_url":"https://digitalcommons.wayne.edu/do/oai/"},"display":{"title":"Parameter Identification And Fault Detection For Reliable Control Of Permanent Magnet Motors","abstract":"<p>The objective of this dissertation is to develop new fault detection, identification, estimation and control algorithms that will be used to detect winding stator fault, identify the motor parameters and optimally control machine during faulty condition. Quality or proposed algorithms for Fault detection, parameter identification and control under faulty condition will validated through analytical study (Cramer-Rao bound) and simulation. Simulation will be performed for three most applied control schemes: Proportional-Integral-Derivative (PID), Direct Torque Control (DTC) and Field Oriented Control (FOC) for Permanent Magnet Machines. New detection schemes forfault detection, isolation and machine parameter identification are presented and analyzed. Different control schemes as PID, DTC, FOC for Control of PM machines have different control loops and therefore it is probable that fault detection and isolation will have different sensitivity. It is very probable that one of these control schemes (PID, DTC or FOC) are more convenient for fault detection and isolation which this dissertation will analyze through computer simulation and, if laboratory condition exist, also running a physical models.</p>","abstract_html":"&lt;p&gt;The objective of this dissertation is to develop new fault detection, identification, estimation and control algorithms that will be used to detect winding stator fault, identify the motor parameters and optimally control machine during faulty condition. Quality or proposed algorithms for Fault detection, parameter identification and control under faulty condition will validated through analytical study (Cramer-Rao bound) and simulation. Simulation will be performed for three most applied control schemes: Proportional-Integral-Derivative (PID), Direct Torque Control (DTC) and Field Oriented Control (FOC) for Permanent Magnet Machines. New detection schemes forfault detection, isolation and machine parameter identification are presented and analyzed. Different control schemes as PID, DTC, FOC for Control of PM machines have different control loops and therefore it is probable that fault detection and isolation will have different sensitivity. It is very probable that one of these control schemes (PID, DTC or FOC) are more convenient for fault detection and isolation which this dissertation will analyze through computer simulation and, if laboratory condition exist, also running a physical models.&lt;/p&gt;","abstract_has_math":false,"creators":["Progovac, Dusan Vukosav"],"institution":null,"degree_name":"Ph.D.","degree_level":"Open Access Dissertation","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Le Yi Wang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2014,"date_issued":"2014-01-01T08:00:00Z","date_published":"2014-01-01T08:00:00Z","updated_at":"2026-07-24T05:59:39Z","subjects":["control","electrical motors","fault detection","identification","least squares","robust","Electrical and Computer Engineering","Other Earth Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.wayne.edu/oa_dissertations/972","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Le Yi Wang"]},{"key":"dc:creator","label":"Author","values":["Progovac, Dusan Vukosav"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2014-01-01T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Open Access Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["control","electrical motors","fault detection","identification","least squares","robust","Electrical and Computer Engineering","Other Earth Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.wayne.edu/oa_dissertations/972"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["<p>The objective of this dissertation is to develop new fault detection, identification, estimation and control algorithms that will be used to detect winding stator fault, identify the motor parameters and optimally control machine during faulty condition. Quality or proposed algorithms for Fault detection, parameter identification and control under faulty condition will validated through analytical study (Cramer-Rao bound) and simulation. Simulation will be performed for three most applied control schemes: Proportional-Integral-Derivative (PID), Direct Torque Control (DTC) and Field Oriented Control (FOC) for Permanent Magnet Machines. New detection schemes forfault detection, isolation and machine parameter identification are presented and analyzed. Different control schemes as PID, DTC, FOC for Control of PM machines have different control loops and therefore it is probable that fault detection and isolation will have different sensitivity. It is very probable that one of these control schemes (PID, DTC or FOC) are more convenient for fault detection and isolation which this dissertation will analyze through computer simulation and, if laboratory condition exist, also running a physical models.</p>"]},{"key":"dc:title","label":"Title","values":["Parameter Identification And Fault Detection For Reliable Control Of Permanent Magnet Motors"]}]}],"canonical_facts":{"dc:contributor":["Le Yi Wang"],"dc:creator":["Progovac, Dusan Vukosav"],"dc:date.available":["2014-01-01T08:00:00Z"],"dc:description.abstract":["<p>The objective of this dissertation is to develop new fault detection, identification, estimation and control algorithms that will be used to detect winding stator fault, identify the motor parameters and optimally control machine during faulty condition. Quality or proposed algorithms for Fault detection, parameter identification and control under faulty condition will validated through analytical study (Cramer-Rao bound) and simulation. Simulation will be performed for three most applied control schemes: Proportional-Integral-Derivative (PID), Direct Torque Control (DTC) and Field Oriented Control (FOC) for Permanent Magnet Machines. New detection schemes forfault detection, isolation and machine parameter identification are presented and analyzed. Different control schemes as PID, DTC, FOC for Control of PM machines have different control loops and therefore it is probable that fault detection and isolation will have different sensitivity. It is very probable that one of these control schemes (PID, DTC or FOC) are more convenient for fault detection and isolation which this dissertation will analyze through computer simulation and, if laboratory condition exist, also running a physical models.</p>"],"dc:identifier":["https://digitalcommons.wayne.edu/oa_dissertations/972"],"dc:subject":["control","electrical motors","fault detection","identification","least squares","robust","Electrical and Computer Engineering","Other Earth Sciences"],"dc:title":["Parameter Identification And Fault Detection For Reliable Control Of Permanent Magnet Motors"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_level":["Open Access Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T05:59:39Z"}