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Relevant bibliographies by topics / Control uncertainty / Dissertations / Theses

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Dissertations / Theses on the topic 'Control uncertainty'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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1

Chellaboina, Vijaya-Sekhar. "Robust stability and performance for linear and nonlinear uncertain systems with structured uncertainty." Diss., Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/12903.

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2

Giftsun, Nirmal. "Handling uncertainty and variability in robot control." Thesis, Toulouse, INSA, 2017. http://www.theses.fr/2017ISAT0028/document.

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Parmi les nombreuses recherches en matière de planification et de contrôle des mouvements pour des applications robotiques, l'humanité n'a jamais atteint un point où les robots seraient parfaitement fonctionnels et autonomes dans des environnements dynamiques. Bien qu'il soit controversé de discuter de la nécessité de ces robots, il est très important d'aborder les problèmes qui nous empêchent de réaliser un tel niveau d'autonomie. Ce travail de recherche tente de résoudre ces problèmes qui séparent ces deux modes de fonctionnement avec un accent particulier sur les incertitudes. Les impossibi

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3

Rodrigues, Júnior Waldery. "Multidimensional robust control, uncertainty and finance." reponame:Repositório Institucional da UnB, 2006. http://repositorio.unb.br/handle/10482/5739.

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Tese (doutorado)—Universidade de Brasília, Departamento de Economia, Programa de Pós-Graduação em Economia, 2006.<br>Submitted by Suelen Silva dos Santos (suelenunb@yahoo.com.br) on 2010-06-22T15:26:15Z No. of bitstreams: 1 2006_WalderyRodriguesJunior.pdf: 1178236 bytes, checksum: 62fc5d96cab6c0e8c1e5a91b9c26e164 (MD5)<br>Approved for entry into archive by Marília Freitas(marilia@bce.unb.br) on 2010-10-22T15:44:18Z (GMT) No. of bitstreams: 1 2006_WalderyRodriguesJunior.pdf: 1178236 bytes, checksum: 62fc5d96cab6c0e8c1e5a91b9c26e164 (MD5)<br>Approved for entry into archive by Carolina Campos(

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4

Warren, Adam L. "Sequential decision-making under uncertainty /." *McMaster only, 2004.

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5

Loh, A. P. "Uncertainty estimation and multivariable control system design." Thesis, University of Oxford, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.375267.

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6

Krueger, David Lawrence. "Parametric uncertainty reduction in robust multivariable control." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1993. http://handle.dtic.mil/100.2/ADA273412.

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Dissertation (Ph.D. in Electrical Engineering) Naval Postgraduate School, September 1993.<br>Dissertation supervisor(s): Burl, Jeffery B. ; Cristi, Roberto. "September 1993." Bibliography: p. 91-91. Also available online.

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7

Herzallah, Randa. "Exploiting uncertainty in nonlinear stochastic control problem." Thesis, Aston University, 2003. http://publications.aston.ac.uk/13267/.

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This work introduces a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelle

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8

Wilson, Mark. "Beyond control : towards an ecology of uncertainty." Thesis, University of Cumbria, 2012. http://insight.cumbria.ac.uk/id/eprint/4371/.

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With specific reference to five discrete projects, this supporting text sets out to explain the methodologies, dynamics and rationale behind the installation-based and collaborative art practice of Snæbjörnsdóttir/Wilson, in relation to contemporary art methodologies and the chronologically parallel and equally emergent academic fields of Artistic Research and Animal Studies. The projects are represented by four monographs and one book chapter, each of which has its basis in a substantial art project involving a sustained period of interdisciplinary research and practice and involving one or

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9

Nagengast, Arne Johannes. "Uncertainty and optimality in human motor control." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608786.

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10

Laiseca, Mario. "Tuning robust control systems under parametric uncertainty." Case Western Reserve University School of Graduate Studies / OhioLINK, 1994. http://rave.ohiolink.edu/etdc/view?acc_num=case1057590557.

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11

Schuur, F. "Action, time, and uncertainty : two types of temporal uncertainty in cognitive motor control." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1370579/.

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Time is a fundamental dimension of cognition and motor control. Preparation for imperative events, choosing the appropriate time to act if there are no external triggers, or deciding between action alternatives if their outcome depends on accurate timing, requires accurate estimates of time. Typically, the accuracy of such estimates is limited and we experience temporal uncertainty. I here distinguish between two types of temporal uncertainty: (a) external temporal uncertainty (ETU), which arises when the timing of imperative events is variable and (b) internal temporal uncertainty (ITU), aris

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12

Quinn, Shannon Leigh. "Measuring and predicting uncertainty in control-relevant statistics." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape8/PQDD_0007/NQ42969.pdf.

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13

Montero, Juan-Pablo. "Uncertainty and the markets for water pollution control." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/36315.

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14

Douglas, Joel S. (Joel Seth). "Linear quadratic control for systems with structured uncertainty." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/35358.

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15

Campbell, Mark E. (Mark Eric) 1968. "Uncertainty modeling for structural control analysis and synthesis." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/49602.

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16

Qin, Li. "Uncertainty, robust control and optimal monetary policy design." Université Louis Pasteur (Strasbourg) (1971-2008), 2008. http://www.theses.fr/2008STR1EC06.

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Cette thèse étudie l'influence de la prise en compte de l'incertitude sur la conduite de politiques monétaires. En adoptant le cadre d'analyse du contrôle robuste développé par Hansen et Sargent (2003), ce travail examine les comportements des autorités monétaires et des agents privés sous l'influence de différentes sources d'incertitudes. Notre recherche démontre que la prise en compte de l'incertitude de modèle conduit la banque centrale à réagir de manière plus active en ajustant le taux d'intérêt. Cependant, dans une économie ouverte, l'ampleur de cet ajustement diminue avec le degré d'ouv

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17

Hoops, Christopher Michael. "Uncertainty Analysis for Control Inputs of Diesel Engines." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1282067559.

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18

Buccapatnam, Tirumala Swapna. "Control of Large Scale Networked Systems Under Uncertainty." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1416764356.

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19

Manikas, Andrew Steven. "Essays in inventory decisions under uncertainty." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22647.

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Thesis (Ph. D.)--Management, Georgia Institute of Technology, 2008.<br>Committee Chair: Yih-Long Chang; Committee Member: Paul Griffin; Committee Member: Ravi Subramanian; Committee Member: Soumen Ghosh; Committee Member: Srinagesh Gavirneni.

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20

Charitopoulos, Vasileios. "Uncertainty-aware integration of control with process operations and multi-parametric programming under global uncertainty." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10061518/.

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Advanced decision making in the process industries requires efficient use of information available at the different hierarchical levels. However, given the time and decision space sparsity the consideration of such integrated problems poses a plethora of challenges. It is goal of the present thesis to present some recent algorithmic and modelling developments with special focus on the uncertainty aware integration of control with process operations. To this end, the thesis comprises of two parts that are orchestrated towards the attainment of the aforestated goal. The first part discusses theo

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21

Nevin, Anne. "The Uncertainty of Decisions in Measurement Based Admission Control." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for telematikk, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-11561.

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Most real-time voice and video applications are delay/loss sensitive but relaxed in the sense that they can tolerate some packet loss/delay. Using this information, network utilization can be greatly improved by exploiting statistical multiplexing. To this end, Measurement Based Admission Control (MBAC) has for a long time been recognized as a promising solution. MBAC algorithms, do not require an a priori source characterization which in many cases may be difficult or impossible to attain. Instead, MBAC uses measurements to capture the behavior of existing flows and uses this information tog

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22

McFarlane, Patrick Kough. "Analysis and uncertainty of airport pushback rate control policies." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/103449.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 111-112).<br>This thesis analyzes the effects of two algorithms that control the departure of aircraft at congested airports, with an emphasis on the uncertainty of the underlying processes. These algorithms, N-control and dynamic programming, belong to a broader class of control policies called Pushback Rate Control (PRC) policies that calculate a pushback rate for departing aircraft based on the state of

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23

Richetta, Octavio. "Ground holding strategies for air traffic control under uncertainty." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/27983.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1991.<br>Includes bibliographical references (leaves 126-127).<br>by Octavio Richetta.<br>Ph.D.

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24

Walker, Daniel James. "Robust control of discrete time systems." Thesis, Imperial College London, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321140.

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25

Wang, Jun. "Generalized multi objective control with application to vehicle suspension systems." Thesis, University of Leeds, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.275799.

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26

Ding, Zhengtao. "Dynamic model uncertainty and change detection with application to a diesel engine." Thesis, University of Manchester, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292779.

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27

Bland, Amy Rachel. "A role for cognitive control in decision making under uncertainty." Thesis, University of Leeds, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.582108.

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Decision-making relies on one's ability to form a stable representation of the underlying Stimulus-Response-Outcome (S-R-O) rules learned from previous experience of gains and losses (e.g. Seymour et al., 2007; Ridderinkhof et al., 2004; Sutton and Barto, 1998). However, learning these representations is made particularly challenging by frequent changes in S-R-O associations. Therefore a changing and volatile world requires continuous tracking of the S-R-O probabilities in our environment (Behrens, et al., 2007; Krugel et al., 2009; N assar et al., 2010). Computational modelling of behaviour t

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28

Tan, Nusret. "Robust analysis and design of control systems with parametric uncertainty." Thesis, University of Sussex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.299029.

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29

Douglas, Joel S. (Joel Seth). "Identification of parametric uncertainty for the control of flexible structures." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/36562.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.<br>Includes bibliographical references (leaves 152-158).<br>by Joel S. Douglas.<br>Ph.D.

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30

How, Jonathan P. "Robust control design with real parameter uncertainty using absolute stability." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12538.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1993.<br>GRSN 640480<br>Includes bibliographical references (p. 185-198).<br>by Jonathan P. How.<br>Ph.D.

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31

Guan, Charlie Zeyu. "Efficient planning for near-optimal contact-rich control under uncertainty." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120435.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2018.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 91-95).<br>Path planning classically focuses on avoiding environmental contact. However, some assembly tasks permit contact through compliance, and such contact may allow for more efficient and reliable solutions under action uncertainty. But optimal manipulation plans that leverage environmental contact are difficult to compute. Environmental contact produces complex kinematics that create difficulties for

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32

Bansal, Vikrant. "Analysis, design and control optimization of process systems under uncertainty." Thesis, Imperial College London, 2000. http://hdl.handle.net/10044/1/8212.

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33

Li, Hongyi. "Robust control design for vehicle active suspension systems with uncertainty." Thesis, University of Portsmouth, 2012. https://researchportal.port.ac.uk/portal/en/theses/robust-control-design-for-vehicle-active-suspension-systems-with-uncertainty(5f7f911c-288e-4868-b82b-154598d5b6d8).html.

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A vehicle active suspension system, in comparison with its counterparts, plays a crucial role in adequately guarantee the stability of the vehicle and improve the suspension performances. With a full understanding of the state of the art in vehicle control systems, this thesis identifies key issues in robust control design for active suspension systems with uncertainty, contributes to enhance the suspension performances via handling tradeoffs between ride comfort, road holding and suspension deflection. Priority of this thesis is to emphasize the contributions in handing actuator-related chall

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34

Lee, Hyun Cheol. "Robust design of control charts for autocorrelated processes with model uncertainty." Texas A&M University, 2004. http://hdl.handle.net/1969.1/2778.

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Statistical process control (SPC) procedures suitable for autocorrelated processes have been extensively investigated in recent years. The most popular method is the residual-based control chart. To implement this method, a time series model, which is usually an autoregressive moving average (ARMA) model, of the process is required. However, the model must be estimated from data in practice and the resulting ARMA modeling errors are unavoidable. Residual-based control charts are known to be sensitive to ARMA modeling errors and often suffer from inflated false alarm rates. As an alternative, c

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35

Haines, Susan Lesley. "Using dynamic rough sets to capture behavioural uncertainty : a space based modelling approach." Thesis, University of York, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.387622.

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36

Kim, Sean Hay. "Development of robust building energy demand-side control strategy under uncertainty." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41115.

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The potential of carbon emission regulations applied to an individual building will encourage building owners to purchase utility-provided green power or to employ onsite renewable energy generation. As both cases are based on intermittent renewable energy sources, demand side control is a fundamental precondition for maximizing the effectiveness of using renewable energy sources. Such control leads to a reduction in peak demand and/or in energy demand variability, therefore, such reduction in the demand profile eventually enhances the efficiency of an erratic supply of renewable energy. The c

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37

Hamisu, Aminu Alhaji. "Petroleum refinery scheduling with consideration for uncertainty." Thesis, Cranfield University, 2015. http://dspace.lib.cranfield.ac.uk/handle/1826/9411.

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Scheduling refinery operation promises a big cut in logistics cost, maximizes efficiency, organizes allocation of material and resources, and ensures that production meets targets set by planning team. Obtaining accurate and reliable schedules for execution in refinery plants under different scenarios has been a serious challenge. This research was undertaken with the aim to develop robust methodologies and solution procedures to address refinery scheduling problems with uncertainties in process parameters. The research goal was achieved by first developing a methodology for short-term crude o

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38

Toktas, Berkin. "Addressing capacity uncertainty in resource-constrained assignment problems /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/10678.

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39

Zhao, Mingjun. "Essays on model uncertainty in macroeconomics." Columbus, Ohio : Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1153244452.

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40

Hellander, Anja. "Multi-Hypothesis Motion Planning under Uncertainty Using Local Optimization." Thesis, Linköpings universitet, Reglerteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-166582.

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Motion planning is defined as the problem of computing a feasible trajectory for an agent to follow. It is a well-studied problem with applications in fields such as robotics, control theory and artificial intelligence. In the last decade there has been an increased interest in algorithms for motion planning under uncertainty where the agent does not know the state of the environment due to, e.g. motion and sensing uncertainties. One approach is to generate an initial feasible trajectory using for example an algorithm such as RRT* and then improve that initial trajectory using local optimizati

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41

Sue, Wing Ian, A. Denny Ellerman, and Jaemin Song. "Absolute vs. Intensity Limits for CO2 Emission Control: Performance Under Uncertainty." MIT Joint Program on the Science and Policy of Global Change, 2006. http://hdl.handle.net/1721.1/31204.

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We elucidate the differences between absolute and intensity-based limits of CO2 emission when there is uncertainty about the future. We demonstrate that the two limits are identical under certainty, and rigorously establish their relative attractiveness under two criteria: preservation of expectations—the minimization of the difference between the actual level and the initial expectation of abatement associated with a one-shot emission target, and temporal stability—the minimization of the variance of abatement due to fluctuations in emissions and GDP over time. Empirical tests of these theore

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42

Adida, Elodie. "Dynamic pricing and inventory control : no backorders under uncertainty and competition." Saarbrücken VDM, Müller, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=2989940&prov=M&dokv̲ar=1&doke̲xt=htm.

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43

Zang, Yong, and 臧勇. "Robust tests under genetic model uncertainty in case-control association studies." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46419123.

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44

Pi, Alexander 1978. "Effects of uncertainty on closed loop shape control in stretch forming." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/89895.

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45

Sujan, Vivek Anand 1972. "Compensating for model uncertainty in the control of cooperative field robots." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8021.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2002.<br>Includes bibliographical references (p. 113-123).<br>Current control and planning algorithms are largely unsuitable for mobile robots in unstructured field environment due to uncertainties in the environment, task, robot models and sensors. A key problem is that it is often difficult to directly measure key information required for the control of interacting cooperative mobile robots. The objective of this research is to develop algorithms that can compensate for these uncertainties and limitation

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46

CORNEJO, GIANN CARLO. "FEEDBACK CONTROL DESIGN USING TEMPLATE BOUNDARIES FOUND THROUGH A PRUNING ALGORITHM FOR PLANTS WITH PARAMETRIC UNCERTAINTY." University of Cincinnati / OhioLINK, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1069447568.

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47

Kennedy, Joseph L. Fales Roger. "Force control of a hydraulic servo system." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/6582.

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The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on November 18, 2009). Thesis advisor: Dr. Roger Fales. Includes bibliographical references.

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48

Gibson, Nathan Scott. "H-infinity Control of Active Magnetic Bearings: An Intelligent Uncertainty Modeling Approach." NCSU, 2004. http://www.lib.ncsu.edu/theses/available/etd-11302004-135840/.

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Robust control techniques require a dynamic model of the plant and bounds on model uncertainty to formulate control laws with guaranteed stability. Although techniques for modeling and identifying dynamic systems are well established, very few procedures exist for estimating uncertainty bounds. In the case of H-infinity control synthesis, a conservative weighting function for model uncertainty is usually chosen to ensure closed-loop stability over the entire operating space. The primary drawback of this conservative, "hard computing" approach is reduced performance due to the number of plants

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49

Hadjiyiannis, Michael Jason. "Decision under uncertainty : problems in control theory, robust optimization and game theory." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/24965.

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Decision making under uncertainty is a widely-studied area spanning a number of fields such as computational optimization, control theory, utility theory and game theory. A typical problem of decision making under uncertainty requires the design of an optimal decision rule, control policy, or behavioural function, that takes into account all available information regarding the uncertain parameters and returns the decision that is most suitable for the given objective. A popular requirement is to determine robust decisions that maintain certain desired characteristics despite the presence of un

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50

Adida, Elodie. "Dynamic pricing and inventory control with no backorders under uncertainty and competition." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36224.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2006.<br>Includes bibliographical references (p. 271-284).<br>Recently, revenue management has become popular in many industries such as the airline, the supply chain, and the transportation industry. Decision makers realize that even small improvements in their operations can have a significant impact on their profits. Nevertheless, determining pricing and inventory optimal policies in more realistic settings may not be a tractable task. Ignoring the potential inaccuracy of paramete

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