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Dissertations / Theses on the topic 'System identification and control'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 February 2023

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1

Szabo, Andrew P. "System Identification and Model-Based Control of Quadcopter UAVs." Wright State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=wright1553197265058507.

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2

Li, Liangmin. "Continuous time nonlinear system identification." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.341867.

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3

Brunke, Shelby Scott. "Nonlinear filtering and system identification algorithms for autonomous systems /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/7095.

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4

Haider, Usama. "Smart Maintenance using System Identification." Thesis, Högskolan i Gävle, Avdelningen för elektroteknik, matematik och naturvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-30735.

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This project discusses the use of System Identification for Smart Maintenance. System Identification is the process of finding a mathematical model of a system using empirical data. The mathematical model can then be used to detect and predict the maintenance needs, which is considered as Smart Maintenance. Smart maintenance strategies have gained pretty much importance recently, since it contributes to economically sustainable production. This project uses the LAVA-framework, proposed in [1] for non-linear system identification, which has the capability of explaining the dynamics of the syste

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5

Salam, Md Abdul, and Md Mafizul Islam. "Modelling and Control System Design to control Water temperature in Heat Pump." Thesis, Karlstads universitet, Avdelningen för fysik och elektroteknik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-30680.

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The thesis has been conducted at Hetvägg AB and the aim is to develop a combined PID and Model Predictive Controller (MPC) controller for an air to water heat pump system that supplies domestic hot water (DHW) to the users. The current control system is PLC based but because of its big size and expensive maintenance it must be replaced with a robust controller for the heat pump. The main goal of this project has been to find a suitable improvement strategy. By constructing a model of the system, the control system has been evaluated. First a model of the system is derived using system identifi

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6

Kristinsson, Kristinn. "Genetic algorithms in system identification and control." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/29628.

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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

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7

Tayamon, Soma. "Nonlinear system identification with applications to selective catalytic reduction systems." Licentiate thesis, Uppsala universitet, Avdelningen för systemteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-186963.

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The stringent regulations on the emissions levels of heavy duty vehicles create a demand for new methods of reducing harmful emissions from the engine. In order to be able to follow these increasingly stricter legislations, complex aftertreatment systems are used. Achievement of optimal performance of these systems requires accurate models that can be used for control design. As a result, the interest in modelling and control of aftertreatment systems has increased. This thesis deals with the modelling of the nitrogen oxide (NOx) emissions from heavy duty vehicles using the selective catalyst

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8

Liu, Xing. "System identification and prediction using neural networks." Thesis, Cardiff University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388229.

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9

Lee, James X. "On fuzzy logic systems, nonlinear system identification, and adaptive control." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/nq26881.pdf.

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10

Lee, James X. (James Xiang) Carleton University Dissertation Engineering Mechanical and Aerospace. "On fuzzy logic systems, nonlinear system identification, and adaptive control." Ottawa, 1997.

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11

Wang, Limin. "Modeling and real-time feedback control of MEMS device." Morgantown, W. Va. : [West Virginia University Libraries], 2004. https://etd.wvu.edu/etd/controller.jsp?moduleName=documentdata&jsp%5FetdId=3711.

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Thesis (Ph. D.)--West Virginia University, 2004.<br>Title from document title page. Document formatted into pages; contains v, 132 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 128-132).

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12

Sharma, Aman. "System Identification of a Micro Aerial Vehicle." Thesis, Luleå tekniska universitet, Rymdteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-73070.

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The purpose of this thesis was to implement an Model Predictive Control based system identification method on a micro-aerial vehicle (DJI Matrice 100) as outlined in a study performed by ETH Zurich. Through limited test flights, data was obtained that allowed for the generation of first and second order system models. The first order models were robust, but the second order model fell short due to the fact that the data used for the model was not sufficient.

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13

Myklebust, Andreas. "Closed Loop System Identification of a Torsion System." Thesis, Linköping University, Department of Electrical Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-17531.

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<p>A model is developed for the Quanser torsion system available at Control Systems Research Laboratory at Chulalongkorn University. The torsion system is a laboratory equipment that is designed for the study of position control. It consists of a DC motor that drives three inertial loads that are coupled in series with the motor, and where all components are coupled to each other through torsional springs.</p><p>Several nonlinearities are observed and the most significant one is an offset in the input signal, which is compensated for. Experiments are carried out under feedback as the system is

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14

Markusson, Ola. "Model and System Inversion with Applications in Nonlinear System Identification and Control." Doctoral thesis, KTH, Signals, Sensors and Systems, 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3287.

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15

Anderson, Jeremiah P. "State-space modeling, system identification and control of a 4th order rotational mechanical system." Thesis, Monterey, California : Naval Postgraduate School, 2009. http://edocs.nps.edu/npspubs/scholarly/theses/2009/Dec/09Dec%5FAnderson.pdf.

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Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, December 2009.<br>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.

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16

Tayamon, Soma. "Nonlinear System Identification and Control Applied to Selective Catalytic Reduction Systems." Doctoral thesis, Uppsala universitet, Avdelningen för systemteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-229148.

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The stringent regulations of emission levels from heavy duty vehicles create a demand for new methods for reducing harmful emissions from diesel engines. This thesis deals with the modelling of the nitrogen oxide (NOx) emissions from heavy duty vehicles using a selective catalyst as an aftertreatment system, utilising ammonia (NH3) for its reduction. The process of the selective catalytic reduction (SCR) is nonlinear, since the result of the chemical reactions involved depends on the load operating point and the temperature. The purpose of this thesis is to investigate different methods for no

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17

Mårtensson, Jonas. "Geometric analysis of stochastic model errors in system identification." Doctoral thesis, KTH, Reglerteknik, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4506.

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Models of dynamical systems are important in many disciplines of science, ranging from physics and traditional mechanical and electrical engineering to life sciences, computer science and economics. Engineers, for example, use models for development, analysis and control of complex technical systems. Dynamical models can be derived from physical insights, for example some known laws of nature, (which are models themselves), or, as considered here, by fitting unknown model parameters to measurements from an experiment. The latter approach is what we call system identification. A model is always

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18

Liu, Zhang. "Structured semidefinite programs in system identification and control." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=2026920931&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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19

Barenthin, Märta. "On input design in system identification for control." Licentiate thesis, KTH, School of Electrical Engineering (EES), 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4000.

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<p>There are many aspects to consider when designing system identification experiments in control applications. Input design is one important issue. This thesis considers input design both for identification of linear time-invariant models and for stability validation.</p><p>Models obtained from system identification experiments are uncertain due to noise present in measurements. The input spectrum can be used to shape the model quality. A key tool in input design is to introduce a linear parametrization of the spectrum. With this parametrization a number of optimal input design problems can b

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Barenthin, Märta. "On input design in system identification for control /." Stockholm : Automatic control, School of Electrical Engineering, Royal Institute of Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4000.

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21

DeVilbiss, Stewart L. "System Identification for H(Infinity) Robust Control Design /." The Ohio State University, 1994. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487859313345322.

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22

Lan, Jing. "Gaussian mixture model based system identification and control." [Gainesville, Fla.] : University of Florida, 2006. http://purl.fcla.edu/fcla/etd/UFE0014640.

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23

Zhou, Xiangrong, and 周向榮. "An integrated approach to identification and control system design." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31241414.

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24

Choi, Eric M. "The modeling and system identification of the Dynamics Identification and Control Experiment." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq29363.pdf.

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25

Lyzell, Christian. "Initialization Methods for System Identification." Licentiate thesis, Linköping University, Linköping University, Automatic Control, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-51688.

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<p>In the system identification community a popular framework for the problem of estimating a parametrized model structure given a sequence of input and output pairs is given by the prediction-error method. This method tries to find the parameters which maximize the prediction capability of the corresponding model via the minimization of some chosen cost function that depends on the prediction error. This optimization problem is often quite complex with several local minima and is commonly solved using a local search algorithm. Thus, it is important to find a good initial estimate for the loca

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26

Guidi, Hernan. "Open and closed-loop model identification and validation." Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-07032009-170311/.

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27

Chowdhary, Mahesh. "On-line system identification for control system applications in particle accelerators." W&M ScholarWorks, 1997. https://scholarworks.wm.edu/etd/1539623898.

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Particle accelerators require a number of feedback systems in order to stabilize a variety of parameters. The Continuous Electron Beam Accelerator at Thomas Jefferson National Accelerator Facility presents a unique set of control and identification problems. This accelerator produces a continuous electron beam with energies between 0.5 and 4.0 GeV to be delivered to the experimental halls. In order to meet stringent beam quality requirements specified by the experimental halls, the position and the energy of the electron beam needs to stabilized at various locations in the accelerator.;A numbe

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28

Brus, Linda. "Nonlinear Identification and Control with Solar Energy Applications." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8594.

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29

Khader, Shahbaz Abdul. "System Identification of Active Magnetic Bearing for Commissioning." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-243630.

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Active magnetic bearing (AMB) is an ideal bearing solution for high performance and energy efficient applications. Proper operation of AMB can be achieved only with advanced feedback control techniques. An identified system model is required for synthesizing high performance model based controllers. System identification is the preferred method for obtaining an accurate model. Therefore, it becomes a prerequisite for the commissioning of AMB. System identification for commissioning poses some challenges and special requirements. In this thesis, system identification of AMB is approached within

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30

Hariri, Bassam. "Modelling and identification of S.I. engines for control system design." Thesis, University of Liverpool, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266264.

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31

Eklund, John M. "Aircraft flight control simulation using parallel cascade system identification." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape17/PQDD_0004/MQ28194.pdf.

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32

Spindler, Henry C. (Henry Carlton) 1970. "System identification and optimal control for mixed-mode cooling." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/30334.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.<br>"September 2004."<br>Includes bibliographical references (p. 285-294).<br>The majority of commercial buildings today are designed to be mechanically cooled. To make the task of air conditioning buildings simpler, and in some cases more energy efficient, windows are sealed shut, eliminating occupants' direct access to fresh air. Implementation of an alternative cooling strategy-mixed-mode cooling-is demonstrated in this thesis to yield substantial savings in cooling energy consumption in many U.S.

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33

Lopes, Rafael Anderson Martins. "Aircraft identification applied to closed loop control system design." Instituto Tecnológico de Aeronáutica, 2006. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=904.

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In the present work, the influence of maneuver design for stability derivatives of aerodynamic forces and moments identification in the performance of closed loop control systems is evaluated, where two maneuvers largely used in aeronautical industry - doublet and 3211 - are compared to a maneuver of restricted use in aeronautical industry, but already well known in identification - the PRBS. This evaluation is divided in two steps: in the first, it is performed the identification with each of the maneuvers and then a crosschecking of the obtained models, computing the mean quadratic predictio

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34

González, Rodrigo A. "Consistency and efficiency in continuous-time system identification." Licentiate thesis, KTH, Reglerteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273176.

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Continuous-time system identification deals with the problem of building continuous-time models of dynamical systems from sampled input and output data. In this field, there are two main approaches: indirect and direct. In the indirect approach, a suitable discrete-time model is first determined, and then it is transformed into continuous-time. On the other hand, the direct approach obtains a continuous-time model directly from the sampled data. In both approaches there exists a dichotomy between discrete-time data and continuous-time models, which can induce robustness issues and complication

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35

Juillet, Fabien. "Control of convection-dominated flows." Palaiseau, Ecole polytechnique, 2013. http://pastel.archives-ouvertes.fr/docs/01/00/94/63/PDF/PhD_Juillet_Fabien.pdf.

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Cette thèse s'intéresse à la mise en œuvre d'une technique de contrôle d'écoulements, d'un point de vue à la fois numérique et expérimental. L'objectif de cette technique est la réduction de perturbations au sein d'écoulements dominés par la convection. Dans ce but, trois aspects sont développés au sein d'un première partie. On observe tout d'abord que dans de tels systèmes l'information voyage essentiellement vers l'aval. Pour cette raison les perturbations doivent être mesurées le plus tôt possible, en plaçant les capteurs en amont. Cette idée intuitive est étudiée quantitativement en introd

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36

Kramer, Boris Martin Josef. "Model and Data Reduction for Control, Identification and Compressed Sensing." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/75179.

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This dissertation focuses on problems in design, optimization and control of complex, large-scale dynamical systems from different viewpoints. The goal is to develop new algorithms and methods, that solve real problems more efficiently, together with providing mathematical insight into the success of those methods. There are three main contributions in this dissertation. In Chapter 3, we provide a new method to solve large-scale algebraic Riccati equations, which arise in optimal control, filtering and model reduction. We present a projection based algorithm utilizing proper orthogonal decompo

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37

Silva, Seth F. "Applied System Identification for a Four Wheel Reaction Wheel Platform." DigitalCommons@CalPoly, 2010. https://digitalcommons.calpoly.edu/theses/328.

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Applied System Identification for a Four Wheel Reaction Wheel Platform By Seth Franklyn Silva At the California Polytechnic State University, San Luis Obispo there is a four-wheel reaction wheel pyramidal simulator platform supported by an air-bearing. This simulator has the current capability to measure the wheel speeds and angular velocity of the platform, and with these measurements, the system identification process was used to obtain the mass properties of this simulator. A handling algorithm was developed to allow wireless data acquisition and command to the spacecraft simulator from a

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38

Merkoulova, Daniel. "Optimal Input Design by Model Predictive Control for System Identification." Thesis, KTH, Reglerteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-215712.

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Mathematical models are an essential part of analysis of autonomous systemsas they ease the formulation of control laws and allow experiments tobe performed in a simulation environment. For complex systems, parts of themodel may be missing which increases uncertainties and limits practical applications.Using input-output measurements makes it possible to estimate themodel, but requires the measurements to be informative. The idea in so-calledinput design is to find an input sequence for the system such that the measurementsreveal the properties and dynamics of the true system as much aspossibl

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39

Brunell, Brent Jerome 1972. "A system identification approach to active control of thermoacoustic instabilities." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/88832.

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40

Rathnasingham, Ruben. "System identification and active control of a turbulent boundary layer." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/10468.

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41

Pietersen, Willem Hermanus. "System identification for fault tolerant control of unmanned aerial vehicles." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4164.

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Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2010.<br>ENGLISH ABSTRACT: In this project, system identification is done on the Modular Unmanned Aerial Vehicle (UAV). This is necessary to perform fault detection and isolation, which is part of the Fault Tolerant Control research project at Stellenbosch University. The equations necessary to do system identification are developed. Various methods for system identification is discussed and the regression methods are implemented. It is shown how to accommodate a sudden change in aircraft parameters due

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42

Demarchi, Fabio Luciano. "Modeling and identification of a fly-by-wire control system." Instituto Tecnológico de Aeronáutica, 2005. http://www.bd.bibl.ita.br/tde_busca/arquivo.php?codArquivo=185.

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This work investigates the system identification and modeling techniques applied to a fly-by-wire system for pitch control of a commercial jet aircraft. The objective of the work is to build a model based on system identification techniques and generic modeling of the system, therefore using the "grey box" approach. The identification data was obtained from experimental tests performed at Embraer "Iron Bird" laboratory. An overview on flight controls systems is presented, focusing on fly-by-wire technology. To provide the theoretical bases for the experimental identification, a review on syst

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43

Choi, Ju-Yeop. "Nonlinear system identification and control using a neural network approach." Diss., Virginia Tech, 1994. http://hdl.handle.net/10919/40199.

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Chang, Gary Carleton University Dissertation Engineering Systems and Computer. "System identification and control of a thermo-mechanical pulping refiner." Ottawa, 1995.

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45

Chamberlain, Caleb H. "System Identification, State Estimation, and Control of Unmanned Aerial Robots." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2605.

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This thesis describes work in a variety of topics related to aerial robotics, including system identification, state estimation, control, and path planning. The path planners described in this thesis are used to guide a fixed-wing UAV along paths that optimize the aircraft's ability to track a ground target. Existing path planners in the literature either ignore occlusions entirely, or they have limited capability to handle different types of paths. The planners described in this thesis are novel in that they specifically account for the effect of occlusions in urban environments, and they can

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Lei, Yu. "Functional Regression and Adaptive Control." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/29113.

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The author proposes a novel functional regression method for parameter estimation and adaptive control in this dissertation. In the functional regression method, the regressors and a signal which contains the information of the unknown parameters are either determined from raw measurements or calculated as the functions of the measurements. The novel feature of the method is that the algorithm maps the regressors to the functionals which are represented in terms of customized test functions. The functionals are updated continuously by the evolution laws, and only an infinite number of variable

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Wang, Dawei. "Robust system identification and robust model predictive control with applications to chemical engineering processes." Thesis, The University of Sydney, 2001. https://hdl.handle.net/2123/27788.

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This thesis deals with problems in two closely related research areas, system identification (SYSID) and model predictive control (MPC), which are both important in industrial. process applications. The robustness of SYSID and MPC is the main concern of the thesis. The focus of the first part of the thesis is to develop Robust System Identification Strategies that yield effective and robust estimates of system model and characteristics under the uncertainty of a priori knowledge. The incorporation of the techniques taken from classical system identification approaches as well as robust

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Alukaidey, R. A. S. "Multivariable identification and adaptive control." Thesis, Brunel University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.384517.

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Malmström, Magnus. "Uncertainties in Neural Networks : A System Identification Approach." Licentiate thesis, Linköpings universitet, Reglerteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-174720.

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In science, technology, and engineering, creating models of the environment to predict future events has always been a key component. The models could be everything from how the friction of a tire depends on the wheels slip to how a pathogen is spread throughout society. As more data becomes available, the use of data-driven black-box models becomes more attractive. In many areas they have shown promising results, but for them to be used widespread in safety-critical applications such as autonomous driving some notion of uncertainty in the prediction is required. An example of such a black-b

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Vu, Ky Minh. "System identification, control algorithms and control interval for the Box-Jenkins dynamic model structure." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq25181.pdf.

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