{"id":{"repo_id":"must-thes","oai_identifier":"oai:scholarsmine.mst.edu:doctoral_dissertations-3221"},"canonical_url":"https://search.dev.ndltd.org/etd/must-thes/oai:scholarsmine.mst.edu:doctoral_dissertations-3221","repository":{"repo_id":"must-thes","name":"Missouri University of Science and Technology","base_url":"https://scholarsmine.mst.edu/do/oai/"},"display":{"title":"Neural network control of nonstrict feedback and nonaffine nonlinear discrete-time systems with application to engine control","abstract":"\"In this dissertation, neural networks (NN) approximate unknown nonlinear functions in the system equations, unknown control inputs, and cost functions for two different classes of nonlinear discrete-time systems. Employing NN in closed-loop feedback systems requires that weight update algorithms be stable...Controllers are developed and applied to a nonlinear, discrete-time system of equations for a spark ignition engine model to reduce the cyclic dispersion of heat release\"--Abstract, page iv.","abstract_html":"&quot;In this dissertation, neural networks (NN) approximate unknown nonlinear functions in the system equations, unknown control inputs, and cost functions for two different classes of nonlinear discrete-time systems. Employing NN in closed-loop feedback systems requires that weight update algorithms be stable...Controllers are developed and applied to a nonlinear, discrete-time system of equations for a spark ignition engine model to reduce the cyclic dispersion of heat release&quot;--Abstract, page iv.","abstract_has_math":false,"creators":["Vance, Jonathan B."],"institution":"University of Missouri--Rolla","degree_name":"Ph. D. in Electrical Engineering","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2016,"date_issued":"2016-02-10T08:00:00Z","date_published":"2016-02-10T08:00:00Z","updated_at":"2026-07-24T03:19:38Z","subjects":["Electrical and Computer Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsmine.mst.edu/doctoral_dissertations/2219","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Vance, Jonathan B."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2016-02-10T08:00:00Z"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D. in Electrical Engineering"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Missouri--Rolla"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical and Computer Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsmine.mst.edu/doctoral_dissertations/2219"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["\"In this dissertation, neural networks (NN) approximate unknown nonlinear functions in the system equations, unknown control inputs, and cost functions for two different classes of nonlinear discrete-time systems. Employing NN in closed-loop feedback systems requires that weight update algorithms be stable...Controllers are developed and applied to a nonlinear, discrete-time system of equations for a spark ignition engine model to reduce the cyclic dispersion of heat release\"--Abstract, page iv."]},{"key":"dc:title","label":"Title","values":["Neural network control of nonstrict feedback and nonaffine nonlinear discrete-time systems with application to engine control"]}]}],"canonical_facts":{"dc:creator":["Vance, Jonathan B."],"dc:date.available":["2016-02-10T08:00:00Z"],"dc:description.abstract":["\"In this dissertation, neural networks (NN) approximate unknown nonlinear functions in the system equations, unknown control inputs, and cost functions for two different classes of nonlinear discrete-time systems. Employing NN in closed-loop feedback systems requires that weight update algorithms be stable...Controllers are developed and applied to a nonlinear, discrete-time system of equations for a spark ignition engine model to reduce the cyclic dispersion of heat release\"--Abstract, page iv."],"dc:identifier":["https://scholarsmine.mst.edu/doctoral_dissertations/2219"],"dc:subject":["Electrical and Computer Engineering"],"dc:title":["Neural network control of nonstrict feedback and nonaffine nonlinear discrete-time systems with application to engine control"],"dc:type":["Dissertation - Open Access"],"thesis:degree_name":["Ph. D. in Electrical Engineering"],"thesis:institution_name":["University of Missouri--Rolla"]},"updated_at":"2026-07-24T03:19:38Z"}