State-space modeling, system identification and control of a 4th order rotational mechanical systemAnderson, Jeremiah P. January 2009 (has links) (PDF)
Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, December 2009. / Thesis Advisor(s): Yun, Xiaoping. Second Reader: Julian, Alex. "December 2009." Description based on title screen as viewed on January 26, 2010. Author(s) subject terms: System identification, state-space, pole placement, full state feedback, observer. Includes bibliographical references (p. 91). Also available in print.
Prediction of end-to-end single flow characteristics in best-effort networksShukla, Yashkumar Dipakkumar 29 August 2005 (has links)
The nature of user traffic in coming years will become increasingly multimediaoriented which has much more stringent Quality of Service (QoS) requirements. The current generation of the public Internet does not provide any strict QoS guarantees. Providing Quality of Service (QoS) for multimedia application has been a difficult and challenging problem. Developing predictive models for best-effort networks, like the Internet, would be beneficial for addressing a number of technical issues, such as network bandwidth provisioning, congestion avoidance/control to name a few. The immediate motivation for creating predictive models is to improve the QoS perceived by end-users in real-time applications, such as audio and video. This research aims at developing models for single-step-ahead and multi-stepahead prediction of end-to-end single flow characteristics in best-effort networks. The performance of path-independent predictors has also been studied in this research. Empirical predictors are developed using simulated traffic data obtained from ns-2 as well as for actual traffic data collected from PlanetLab. The linear system identification models Auto-Regressive (AR), Auto-Regressive Moving Average (ARMA) and the non-linear models Feed-forward Multi-layer Perceptron (FMLP) have been used to develop predictive models. In the present research, accumulation is chosen as a signal to model the end-to-end single flow characteristics. As the raw accumulation signal is extremely noisy, the moving average of the accumulation isused for the prediction. Developed predictors have been found to perform accurate single-step-ahead predictions. However, as the multi-step-ahead prediction horizon is increased, the models do not perform as accurately as in the single-step-ahead prediction case. Acceptable multi-step-ahead predictors for up to 240 msec prediction horizon have been obtained using actual traffic data.
A novel subspace identification algorithm and its application in stochastic fault detectionWang, Jin 28 August 2008 (has links)
Not available / text
Two-dimensional dynamic analysis of functionally graded structures by using meshfree boundary-domain integral equation methodYang, Yang January 2015 (has links)
University of Macau / Faculty of Science and Technology / Department of Civil and Environmental Engineering
Structural determination in the development of nonlinear process modelsSchooling, Steven Paul January 1997 (has links)
No description available.
Further investigations of the Dynamic Data System modeling strategy by simulationsKunpanitchakit, Chairote. January 1982 (has links)
Thesis (Ph. D.)--University of Wisconsin--Madison, 1982. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 282-294).
Control loop performance assessment with closed-loop subspace identificationDanesh Pour, Nima. January 2009 (has links)
Thesis (M. Sc.)--University of Alberta, 2009. / Title from PDF file main screen (viewed on Aug. 25, 2009). "A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science in Process Control, Department of Chemical and Materials Engineering, University of Alberta." Includes bibliographical references.
A novel subspace identification algorithm and its application in stochastic fault detectionWang, Jin, Qin, S. Joe, January 2004 (has links) (PDF)
Thesis (Ph. D.)--University of Texas at Austin, 2004. / Supervisor: S. Joe Qin. Vita. Includes bibliographical references.
Hierarchical Identification of Large-Scale System ModelsJankovic, Boris R. January 1997 (has links)
Dissertation submitted in compliance with the requirements for the Doctor's Degree in Technology in the Department of Electrical Engineering (Light Current) at Technikon Natal / In this study we propose a new concept and methodology of hierarchical identification. The need for such a methodology comes from the fact that identification of large-scale systems (LSSs) by one-shot approach may be numerically very complex. The analysis of LSSs is, in general, not approached by the one-shot methodologies normally associated with non-LSSs. The proposed method of hierarchical identification can be therefore viewed as an extension of LSS methodologies to system identification. LSS methodology aims at breaking up the initial, complex problem into a set of smaller size subproblems. / D
Genetic algorithms in system identification and controlKristinsson, Kristinn January 1990 (has links)
Current online identification techniques are recursive and involve local search techniques. In this thesis, we show how genetic algorithms, a parallel, global search technique emulating natural genetic operators can be used to estimate the poles and zeros of a dynamical system. We also design an adaptive controller based on the estimates. The algorithms are shown to be useful for continuous time parameter identifications and to be able to identify directly physical parameters of a system. Simulations and an experiment show the technique to be satisfactory and to provide unbiased estimates in presence of colored noise. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate
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