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dc.contributor.authorDhaliwal, Samandeep Singh
dc.contributor.otherQueen's University (Kingston, Ont.). Theses (Queen's University (Kingston, Ont.))en
dc.date2011-10-31 22:04:58.762en
dc.date.accessioned2011-11-01T17:49:24Z
dc.date.available2011-11-01T17:49:24Z
dc.date.issued2011-11-01
dc.identifier.urihttp://hdl.handle.net/1974/6849
dc.descriptionThesis (Master, Chemical Engineering) -- Queen's University, 2011-10-31 22:04:58.762en
dc.description.abstractThe problem of parameter and state estimation of a class of nonlinear systems is addressed. An adaptive identifier and observer are used to estimate the parameters and the state variables simultaneously. The proposed method is derived using a new formulation. Uncertainty sets are defined for the parameters and a set of auxiliary variables for the state variables. An algorithm is developed to update these sets using the available information. The algorithm proposed guarantees the convergence of parameters and the state variables to their true value. In addition to its application in difficult estimation problems, the algorithm has also been adapted to handle fault detection problems. The technique of estimation is applied to two broad classes of systems. The first involves a class of continuous time nonlinear systems subject to bounded unknown exogenous disturbance with constant parameters. Using the proposed set-based adaptive estimation, the parameters are updated only when an improvement in the precision of the parameter estimates can be guaranteed. The formulation provides robustness to parameter estimation error and bounded disturbance. The parameter uncertainty set and the uncertainty associated with an auxiliary variable is updated such that the set is guaranteed to contain the unknown true values. The second class of system considered is a class of nonlinear systems with timevarying parameters. Using a generalization of the set-based adaptive estimation technique proposed, the estimates of the parameters and state are updated to guarantee convergence to a neighborhood of their true value. The algorithm proposed can also be extended to detect the fault in the system, injected by drastic change in the time-varying parameter values. To study the practical applicability of the developed method, the estimation of state variables and time-varying parameters of salt in a stirred tank process has been performed. The results of the experimental application demonstrate the ability of the proposed techniques to estimate the state variables and time-varying parameters of an uncertain practical system.en_US
dc.languageenen
dc.language.isoenen_US
dc.relation.ispartofseriesCanadian thesesen
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.subjectState Estimationen_US
dc.subjectAdaptive Identifieren_US
dc.subjectNonlinear Systemsen_US
dc.subjectParameter Identificationen_US
dc.subjectAdaptive Observeren_US
dc.titleState Estimation and Parameter Identification of Continuous-time Nonlinear Systemsen_US
dc.typeThesisen_US
dc.description.degreeMasteren
dc.contributor.supervisorGuay, Martinen
dc.contributor.departmentChemical Engineeringen


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