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dc.contributor.authorMoshksar, Ehsan
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2015-09-29 16:55:10.635en
dc.date.accessioned2015-10-03T21:25:44Z
dc.date.available2015-10-03T21:25:44Z
dc.date.issued2015-10-03
dc.identifier.urihttp://hdl.handle.net/1974/13742
dc.descriptionThesis (Ph.D, Chemical Engineering) -- Queen's University, 2015-09-29 16:55:10.635en
dc.description.abstractThis dissertation considers the adaptive estimation of time-varying parameters and its use in extremum-seeking control problems. The ability to estimate uncertain time-varying behaviour can have a significant impact on a control system's performance. Hence, the problem of time-varying parameter estimation has been of considerable interest over the last two decades. The present work provides a formal scheme for time-varying parameter estimation in a class of nonlinear systems. The geometric concept of invariance is the key concept for the parameter estimation techniques developed in this thesis. The techniques use a number of high gain estimators and filters that generate an almost invariant manifold. The almost invariance property allows an implicit mapping and a parameter update law that guarantees exponentially convergence to a small region of the true values of the time-varying parameters. A generalization of the invariant manifold approach is considered to deal with the estimation of periodic parameters with unknown periodicity. In another step, this thesis seeks to apply the proposed time-varying estimation technique to the solution of extremum-seeking control problems. In extremum-seeking control, a gradient descent algorithm is used to find the optimal value of a measured but unknown cost functions. The contribution of this aspect of the thesis is the formulation of the extremum-seeking control problem where the unknown gradient of the cost is estimated as a time-varying parameter using the proposed invariance based estimation technique. The proposed approach is extended for the solution of constrained steady-state optimization problems. We establish two methods for finding the optimal points for systems with unknown objective functions that are subject to unknown/uncertain dynamics. For systems with unknown dynamics, a nonlinear proportional-integral controller is designed to find the optimal solution. Then for a class of control affine systems with known high frequency gains, an inverse optimal control technique is used for the direct design of a gradient-based controller.en_US
dc.languageenen
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
dc.rightsQueen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canadaen
dc.rightsProQuest PhD and Master's Theses International Dissemination Agreementen
dc.rightsIntellectual Property Guidelines at Queen's Universityen
dc.rightsCopying and Preserving Your Thesisen
dc.rightsCreative Commons - Attribution - CC BYen
dc.rightsThis publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.en
dc.subjectExtremum-Seeking Controlen_US
dc.subjectAdaptive Estimationen_US
dc.titleEstimation of Time-Varying Parameters and Its Application to Extremum-Seeking Controlen_US
dc.typethesisen_US
dc.description.degreePh.Den
dc.contributor.supervisorGuay, Martinen
dc.contributor.departmentChemical Engineeringen


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