{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/31127"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/31127","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Inverse optimization of discrete-time systems applied to human locomotion","abstract":"The problem of inverse optimization is to find the objective function that is being minimized, given knowledge of the constraints and observations of local minima. In this thesis, we consider the special case in which the objective function is a linear combination of known basis functions weighted by unknown parameters. Therefore the aim is to recover the weights governing the objective function. We propose a solution approach in this case that is based on the application of necessary conditions for optimality. We begin with a review of how these necessary conditions arise, with a particular focus on the relationship between duality theory and inverse optimization. We then proceed to describe our solution approach. Finally, we apply our approach to find a model of goal-directed human walking from experimental data with human subjects.","abstract_html":"The problem of inverse optimization is to find the objective function that is being minimized, given knowledge of the constraints and observations of local minima. In this thesis, we consider the special case in which the objective function is a linear combination of known basis functions weighted by unknown parameters. Therefore the aim is to recover the weights governing the objective function. We propose a solution approach in this case that is based on the application of necessary conditions for optimality. We begin with a review of how these necessary conditions arise, with a particular focus on the relationship between duality theory and inverse optimization. We then proceed to describe our solution approach. Finally, we apply our approach to find a model of goal-directed human walking from experimental data with human subjects.","abstract_has_math":false,"creators":["Puydupin, Anne-Sophie"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Aerospace Engineering","degree_department":null,"school":null,"contributors":["Bretl, Timothy W."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2012,"date_issued":"2012-05-22T00:29:47Z","date_published":"2012-05-22T00:29:47Z","updated_at":"2026-07-22T22:25:30Z","subjects":["Inverse optimization","optimization","necessary conditions for optimality","duality theory","human locomotion."],"languages":["en"],"rights":["Copyright 2012 Anne-Sophie Gaby Marthe Puydupin."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/31127","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Bretl, Timothy W."]},{"key":"dc:creator","label":"Author","values":["Puydupin, Anne-Sophie"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2012-05-22T00:29:47Z","2012-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Aerospace Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Inverse optimization","optimization","necessary conditions for optimality","duality theory","human locomotion."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2012 Anne-Sophie Gaby Marthe Puydupin."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/31127"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["The problem of inverse optimization is to find the objective function that is being minimized, given knowledge of the constraints and observations of local minima. In this thesis, we consider the special case in which the objective function is a linear combination of known basis functions weighted by unknown parameters. Therefore the aim is to recover the weights governing the objective function. We propose a solution approach in this case that is based on the application of necessary conditions for optimality. We begin with a review of how these necessary conditions arise, with a particular focus on the relationship between duality theory and inverse optimization. We then proceed to describe our solution approach. 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We begin with a review of how these necessary conditions arise, with a particular focus on the relationship between duality theory and inverse optimization. We then proceed to describe our solution approach. Finally, we apply our approach to find a model of goal-directed human walking from experimental data with human subjects.","Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2012-04-26T19:02:03Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Puydupin_AnneSophie.pdf: 813810 bytes, checksum: 156b29555fe3a99ed06a5c5f89f09a1d (MD5)","Made available in DSpace on 2012-05-22T00:29:47Z (GMT). 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