This thesis adresses the problem of estimating the parameters in a permanent magnet synchronous motor (PMSM). There is an uncertainty about the parameters, due to age and tolerances in the manufacturing process. Parameters such as the resistance and the current to torque factor Kt, changes with respect to temperature as well. The temperature in the motor varies in normal motor operation, due to variations in angular velocity and torques. Online estimation methods with the model reference adaptive systems technique (MRAS) and offline methods are presented. The estimation algorithms are validated in simulations with Matlab/Simulink and also evaluated with experimental data. Experiments were performed on a range of different motors, in realistic scenarios. Relevant factors such as the angular velocity of the rotor and the impact of the gravity force are investigated. The results show that it is possible to estimate the motor factor $K_t$, with an accuracy of two percentage from its reference value in normal industry conditions. The estimated value of the motor inductance is within 25 percentage of the calculated reference value. The resistance however is affected by the resistance in the cables from the motor to the measurement device. With the cable resistance included in the calculations, the estimate still often exceeds double the value of the reference value.

A networked control system (NCS) is a feedback control system that has its control loop physically connected via real-time communication networks. To meet the demands of `teleautomation', modularity, integrated diagnostics, quick maintenance and decentralization of control, NCSs have received remarkable attention worldwide during the past decade. Yet despite their distinct advantages, NCSs are suffering from network-induced constraints such as time delays and packet dropouts, which may degrade system performance. Therefore, the network-induced constraints should be incorporated into the control design and related studies.<p> For the problem of state estimation in a network environment, we present the strategy of simultaneous input and state estimation to compensate for the effects of unknown input missing. A sub-optimal algorithm is proposed, and the stability properties are proven by analyzing the solution of a Riccati-like equation.<p> Despite its importance, system identification in a network environment has been studied poorly before. To identify the parameters of a system in a network environment, we modify the classical Kalman filter to obtain an algorithm that is capable of handling missing output data caused by the network medium. Convergence properties of the algorithm are established under the stochastic framework.<p> We further develop an adaptive control scheme for networked systems. By employing the proposed output estimator and parameter estimator, the designed adaptive control can track the expected signal. Rigorous convergence analysis of the scheme is performed under the stochastic framework as well.

Thesis (Ph. D.)--University of Washington, 2000. / Vita. Includes bibliographical references (leaves 164-170).

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, December 2003. / Thesis advisor(s): Roberto Cristi, Fotis A. Papoulias. Includes bibliographical references (p. 155). Also available online.

Thesis (Ph. D.)--University of Toronto, 2004. / Adviser: Ruth Childs. Includes bibliographical references.

Univ., Diss.--Tübingen, 2002. / Includes bibliographical references and index.

Thesis (Ph. D.)--University of Hong Kong, 2008. / Includes bibliographical references (leaf 103-113) Also available in print.

Thesis (M. Phil.)--University of Hong Kong, 2008. / Includes bibliographical references (leaf 101-106) Also available in print.

Thesis (M.S.)--California Polytechnic State University, 2008. / "May 2008." "In partial fulfillment of the requirements for the degree [of] Master of Science in Mechanical Engineering." "Presented to the faculty of California Polytechnic State University, San Luis Obispo." Major professor: John Ridgely, Ph.D. Accompanying CD-ROMs contain software files. Includes bibliographical references (leaf 61). Also available online and on microfiche (2 sheets).

Thesis (Ph. D.)--University of Washington, 1999. / Vita. Includes bibliographical references (leaves 114-121).