{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/106135"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/106135","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"An improved algorithm for identification of time varying parameters using recursive digital techniques","abstract":"Identification is the process of determining values for the characteristic quantities, called parameters, of a system. Examples of such quantities are mass, inductance, resistance, spring coefficient, gain, et cetera. The decreasing cost of digital processors and the versatility of digital programming make digital methods an attractive means of accomplishing identification. It is important, however, that an identifier be able to track any change in a parameter if its output is to be used in any predictive capacity, such as in an adaptive controller. Most studies of digital identification have avoided the topic of time variations by using batch processing methods that implicitly assume constant parameters; this thesis does not. This thesis first investigates the parameter-tracking capabilities of a popular, real-time digital identification algorithm, the recursive weighted least squares method. This method is claimed to be able to track only slowly time-varying parameters. Based on the results of this study, a method of improving the accuracy of estimates of time-varying parameters is developed. This method, called conditioning, is a post-processor to the recursive weighted least squares algorithm. The results of tests of this method using three different plant simulations are presented, demonstrating the improved accuracy achieved by conditioning estimates of time-varying parameters.","abstract_html":"Identification is the process of determining values for the characteristic quantities, called parameters, of a system. Examples of such quantities are mass, inductance, resistance, spring coefficient, gain, et cetera. The decreasing cost of digital processors and the versatility of digital programming make digital methods an attractive means of accomplishing identification. It is important, however, that an identifier be able to track any change in a parameter if its output is to be used in any predictive capacity, such as in an adaptive controller. Most studies of digital identification have avoided the topic of time variations by using batch processing methods that implicitly assume constant parameters; this thesis does not. This thesis first investigates the parameter-tracking capabilities of a popular, real-time digital identification algorithm, the recursive weighted least squares method. This method is claimed to be able to track only slowly time-varying parameters. Based on the results of this study, a method of improving the accuracy of estimates of time-varying parameters is developed. This method, called conditioning, is a post-processor to the recursive weighted least squares algorithm. The results of tests of this method using three different plant simulations are presented, demonstrating the improved accuracy achieved by conditioning estimates of time-varying parameters.","abstract_has_math":false,"creators":["Maloney, Bernard Christopher Patrick"],"institution":"Virginia Polytechnic Institute and State University","degree_name":"M.S.","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1986,"date_issued":"1986","date_published":"1986","updated_at":"2026-07-22T22:19:38Z","subjects":[],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10919/106135","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Maloney, Bernard Christopher Patrick"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2021-10-26T20:10:15Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2021-10-26T20:10:15Z"]},{"key":"dc:date.issued","label":"Date","values":["1986"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Polytechnic Institute and State University"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/106135"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Identification is the process of determining values for the characteristic quantities, called parameters, of a system. 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This method, called conditioning, is a post-processor to the recursive weighted least squares algorithm. The results of tests of this method using three different plant simulations are presented, demonstrating the improved accuracy achieved by conditioning estimates of time-varying parameters."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.S."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["An improved algorithm for identification of time varying parameters using recursive digital techniques"]}]}],"canonical_facts":{"dc:contributor.department":["Mechanical Engineering"],"dc:creator":["Maloney, Bernard Christopher Patrick"],"dc:date.accessioned":["2021-10-26T20:10:15Z"],"dc:date.available":["2021-10-26T20:10:15Z"],"dc:date.issued":["1986"],"dc:description.abstract":["Identification is the process of determining values for the characteristic quantities, called parameters, of a system. Examples of such quantities are mass, inductance, resistance, spring coefficient, gain, et cetera. The decreasing cost of digital processors and the versatility of digital programming make digital methods an attractive means of accomplishing identification. It is important, however, that an identifier be able to track any change in a parameter if its output is to be used in any predictive capacity, such as in an adaptive controller. Most studies of digital identification have avoided the topic of time variations by using batch processing methods that implicitly assume constant parameters; this thesis does not. This thesis first investigates the parameter-tracking capabilities of a popular, real-time digital identification algorithm, the recursive weighted least squares method. This method is claimed to be able to track only slowly time-varying parameters. Based on the results of this study, a method of improving the accuracy of estimates of time-varying parameters is developed. 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The results of tests of this method using three different plant simulations are presented, demonstrating the improved accuracy achieved by conditioning estimates of time-varying parameters."],"dc:description.degree":["M.S."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/10919/106135"],"dc:language.iso":["en"],"dc:publisher":["Virginia Polytechnic Institute and State University"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["An improved algorithm for identification of time varying parameters using recursive digital techniques"],"dc:type":["Thesis"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Mechanical Engineering"],"thesis:degree_level":["masters"],"thesis:degree_name":["M.S."],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:38Z"}