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Dissertations / Theses on the topic 'Predictive control systems'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Scokaert, Pierre O. M. "Constrained predictive control." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359508.

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2

Chang, Anton On Tak. "Multivariable predictive control." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336179.

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3

Shead, Leo R. E. "Predictive control of nonsquare systems." Thesis, University of Sheffield, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.505568.

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4

Ouyang, Hua. "Networked predictive control systems : control scheme and robust stability." Thesis, University of South Wales, 2007. https://pure.southwales.ac.uk/en/studentthesis/networked-predictive-control-systems(9c6178d7-e6a4-420b-b35f-2d62d35ff5b0).html.

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Networked predictive control is a new research method for Networked Control Systems (NCS), which is able to handle network-induced problems such as time-delay, data dropouts, packets disorders, etc. while stabilizing the closed-loop system. This work is an extension and complement of networked predictive control methodology. There is always present model uncertainties or physical nonlinearity in the process of NCS. Therefore, it makes the study of the robust control of NCS and that of networked nonlinear control system (NNCS) considerably important. This work studied the following three proble

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5

Yoon, Tae-Woong. "Robust adaptive predictive control." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359527.

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6

Chow, Chi-Ming. "Predictive control with constraints." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320170.

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7

O'Brien, Marie. "Predictive control of urban wastewater systems." Thesis, University of Strathclyde, 2006. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21658.

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Within recent years, technological advances and stricter regulatory requirements have seen the increased use of automation and instrumentation within the wastewater treatment industry. As a result, advanced control strategies are required, to fully exploit the potential of these complex systems in addressing water quality concerns. Model based control strategies can be appropriate within the multivariable constrained wastewater system. In particular, the inherent model based nature of this approach can be valuable in the prediction of the treatment plant effluent quality required over a consid

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8

Mu, Huiying. "Predictive control of linear uncertain systems." Thesis, Imperial College London, 2007. http://hdl.handle.net/10044/1/8515.

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Predictive control is a very useful tool in controlling constrained systems, since the constraints can be satisfied explicitly by the optimisations. Sets, namely, reachable sets, controllable sets, invariant sets, etc, play fundamental roles in designing predictive control strategies for uncertain systems. Meanwhile, in addition to the commonly assumed boundedness of the uncertainty, the explicit use of its stochastic properties can lead to improvement in system response. This thesis is concerned with robust set theories, mainly for reachable sets, with applications to time-optimal control; an

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9

Bell, Geoffrey Laurence. "Robust model predictive control design." Thesis, Imperial College London, 2000. http://hdl.handle.net/10044/1/7450.

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10

Williams, Grevin Carlton. "Auxiliary measurements in predictive control." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.357555.

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11

Townsend, Shane Martin Joseph. "Non-linear model predictive control." Thesis, Queen's University Belfast, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301061.

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12

Overloop, Peter-Jules van. "Model predictive control on open water systems /." Amsterdam : IOS Press, 2006. http://opac.nebis.ch/cgi-bin/showAbstract.pl?u20=9781586036386.

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13

Segayer, Abdunnaser Mohammed. "Genetic design of robust predictive control systems." Thesis, University of Salford, 2002. http://usir.salford.ac.uk/26902/.

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Despite the fact that PID controllers are undoubtedly the most popular controllers used in industrial control processes for decades, they do not perform well when applied to systems with significant time-delay. Consideration of this problem led to the development of predictive control strategies in the 1950's and lately in the 1980's. Perhaps the best-known predictive control techniques that has received the most attention in the control of long time-delayed plants and used almost exclusively in the process industries are the Smith Predictor Controller (SPC) and more recently the Internal Mode

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14

Atić, Nedz̆ad. "Model predictive control design for load frequency control problem." Morgantown, W. Va. : [West Virginia University Libraries], 2003. http://etd.wvu.edu/templates/showETD.cfm?recnum=3192.

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Thesis (M.S.)--West Virginia University, 2003.<br>Title from document title page. Document formatted into pages; contains vii, 68 p. : ill. Includes abstract. Includes bibliographical references (p. 66-68).

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15

Kassapakis, E. G. "Studies on a predictive control algorithm." Thesis, University of Reading, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.360726.

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16

Kestner, Brian. "Model predictive control (MPC) algorithm for tip-jet reaction drive systems." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/31802.

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Thesis (Ph.D)--Aerospace Engineering, Georgia Institute of Technology, 2010.<br>Committee Chair: Mavris, Dimitri; Committee Member: German, Brian; Committee Member: Healy, Tim; Committee Member: Rosson, Randy; Committee Member: Tai, Jimmy. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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17

Jing, Junbo. "Vehicle Predictive Fuel-Optimal Control for Real-World Systems." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1534506777487814.

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18

CAVANINI, Luca. "Model Predictive Control for Electrical and Mechatronic Systems." Doctoral thesis, Università Politecnica delle Marche, 2018. http://hdl.handle.net/11566/253007.

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L'attività di ricerca presentata in questa tesi riguarda il progetto e lo sviluppo di sistemi di controllo basati sulla predizione del comportamento del processo da controllare, in modo da ottenere prestazioni di controllo ottimizzate. I processi presi in considerazione sono convertitori elettrici di potenza e sistemi meccatronici. L'uso di algoritmi di controllo basati sul modello per predire l'evoluzione del processo è stata limitato a lungo a sistemi caratterizzati da dinamiche lente. Ciò è dovuto al tempo necessario a calcolare la legge di controllo, che prevede la risoluzione di un proble

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19

Suzuki, Hiromi. "Studies on predictive control for constrained linear systems." 京都大学 (Kyoto University), 2007. http://hdl.handle.net/2433/135971.

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20

Kim, Tae-Hyoung. "Robust model predictive control for constrained linear systems." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/143898.

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Kyoto University (京都大学)<br>0048<br>新制・課程博士<br>博士(情報学)<br>甲第12450号<br>情博第204号<br>新制||情||44(附属図書館)<br>24286<br>UT51-2006-J441<br>京都大学大学院情報学研究科システム科学専攻<br>(主査)教授杉江俊治, 教授酒井英昭, 教授熊本博光<br>学位規則第4条第1項該当

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21

Huang, Gongsheng. "Predictive control of highly uncertain and nonlinear systems." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.442848.

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22

Wiltz, Adrian Samuel. "Distributed Robust Model Predictive Control of Multiagent Systems." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278491.

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In this thesis, a distributed model predictive controller (MPC) is developed forthe formation control problem of continuous-time multiagent systems subject tostate constraints, coupling state constraints and input constraints, where all agentssolve their respective local optimization problem in parallel. As coupling stateconstraints, connectivity and collision avoidance constraints are regarded in particular.Consistency constraints, which ensure that an agent’s actual state trajectoryremains in the neighborhood of its previously communicated referencetrajectory, are employed to bound the uncer

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23

Koetje, Thabo. "Multi-objectives model predictive control of multivariable systems." Master's thesis, University of Cape Town, 2011. http://hdl.handle.net/11427/11426.

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24

Lopez, Léo. "Brain-inspired predictive control of robotic sensorimotor systems." Thesis, Université Clermont Auvergne‎ (2017-2020), 2017. http://www.theses.fr/2017CLFAC106.

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25

Lopez, Brett Thomas. "Adaptive robust model predictive control for nonlinear systems." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122395.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2019<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 115-124).<br>Modeling error and external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over control policies but at the expense of computational complexity. An alternative strategy, known as tube MPC, uses a robust controller (designed offline) to keep the system in an invariant tube cen

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26

Colautti, Stefano <1982&gt. "Model predictive flight control systems for rotorcraft UAS." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amsdottorato.unibo.it/3497/1/Colautti_Stefano_tesi.pdf.

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Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the develop

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27

Colautti, Stefano <1982&gt. "Model predictive flight control systems for rotorcraft UAS." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2011. http://amsdottorato.unibo.it/3497/.

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Constraints are widely present in the flight control problems: actuators saturations or flight envelope limitations are only some examples of that. The ability of Model Predictive Control (MPC) of dealing with the constraints joined with the increased computational power of modern calculators makes this approach attractive also for fast dynamics systems such as agile air vehicles. This PhD thesis presents the results, achieved at the Aerospace Engineering Department of the University of Bologna in collaboration with the Dutch National Aerospace Laboratories (NLR), concerning the develop

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28

Lambert, Martin Richard. "Adaptive control of flexible systems." Thesis, University of Oxford, 1987. http://ora.ox.ac.uk/objects/uuid:d19d44f9-b7db-4b00-95be-4cf897450836.

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This thesis reports the successful application of the recently introduced Generalised Predictive Control self-tuner to the high-performance positioning of a real flexible single-link robot arm. The large amount of experimental time available on this high bandwidth system allowed exhaustive testing of the 'tuning-knobs' and 'design-filters' available to the user for tailoring the closed-loop. Based upon these experiments a coherent philosophy for configuring GPC in practice is generated. Configuration details found to be necessary for satisfactory GPC control of this high-order neutrally stable

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29

Henriksson, Erik. "Predictive Control for Wireless Networked Systems in Process Industry." Doctoral thesis, KTH, Reglerteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-141459.

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Wireless networks in industrial process control enable new system architectures and designs. However, wireless control systems can be severely affected by the imperfections of the communication links. This thesis proposes new methods to handle such imperfections by adding additional components in the control loop, or by adapting sampling intervals and control actions. First, the predictive outage compensator is proposed. It is a filter which is implemented at the receiver side of networked control systems. There it generates predicted samples when data are lost, based on past data. The impleme

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30

Boussemart, Yves 1980. "Predictive models of procedural human supervisory control behavior." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/79543.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Engineering Systems Division, 2011.<br>Page 150 blank. Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 138-149).<br>Human supervisory control systems are characterized by the computer-mediated nature of the interactions between one or more operators and a given task. Nuclear power plants, air traffic management and unmanned vehicles operations are examples of such systems. In this context, the role of the operators is typically highly proceduralized due to the time and mission-critical nature of the tasks.

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31

TORCHIO, MARCELLO. "Model Predictive Control Strategies for Advanced Battery Management Systems." Doctoral thesis, Università degli studi di Pavia, 2017. http://hdl.handle.net/11571/1203372.

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Consumer electronics, wearable and personal health devices, power networks, microgrids, and hybrid electric vehicles (HEVs) are some of the many applications where Lithium-ion (Li-ion) batteries are employed. From a manufacturer point of view, the optimal design and management of such electrochemical accumulators are important aspects for ensuring safe and profitable operations. The adoption of mathematical models can support the achievement of the best performance, while saving time and money. In the literature, all the models used to describe the behavior of a Li-ion battery belong to one of

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32

Droge, Greg Nathanael. "Behavior-based model predictive control for networked multi-agent systems." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51864.

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We present a motion control framework which allows a group of robots to work together to decide upon their motions by minimizing a collective cost without any central computing component or any one agent performing a large portion of the computation. When developing distributed control algorithms, care must be taken to respect the limited computational capacity of each agent as well as respect the information and communication constraints of the network. To address these issues, we develop a distributed, behavior-based model predictive control (MPC) framework which alleviates the computational

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33

Gossner, Jesse Ross. "Generalised predictive control in the presence of constraints." Thesis, University of Oxford, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.318601.

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34

Wang, Shensheng. "Weighting normalization in optimal predictive control /." free to MU campus, to others for purchase, 2001. http://wwwlib.umi.com/cr/mo/fullcit?p3025659.

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35

Sun, Congcong. "Multi-layer model predictive control of complex water systems." Doctoral thesis, Universitat Politècnica de Catalunya, 2015. http://hdl.handle.net/10803/326739.

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This thesis is devoted to design a multi-layer MPC controller applied to the complex water network taking into account that the different layers with different time scales and control objectives have their own controller. A two-layer temporal hierarchy coordinating scheme has been applied to coordinate the MPC controllers for the supply and transportation layers. An integrated real-time simulation-optimization approach which contributes to consider the effect of more complex dynamics, better represented by the simulation model, has been developed for regional water networks. The use of the com

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36

Asar, Isik. "Model Predictive Control (mpc) Performance For Controlling Reaction Systems." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605001/index.pdf.

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In this study, the performance of the Model Predictive Controller (MPC) algorithm is investigated in two different reaction systems. The first case is a saponification reaction system where ethyl acetate reacts with sodium hydroxide to produce sodium acetate and ethanol in a CSTR. In the reactor, temperature and sodium acetate concentration are controlled by manipulating the flow rates of ethyl acetate and cooling water. The model of the reactor is developed considering first principal models. The experiments are done to obtain steady state data from the reaction system and these are compared

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37

Henriksson, Erik, Henrik Sandberg, and Karl Henrik Johansson. "Predictive Compensation for Communication Outages in Networked Control Systems." KTH, Reglerteknik, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-58481.

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A predictive outage compensator co-located with the actuator node in a networked control system can be used to counteract unpredictable losses of data in the feedback control loop. When a new control command is not received at the actuator node at an appropriate time instance, the predictive outage compensator suggests a replacement command based on the history of past control commands. It is shown that a simple tuning phase together with the monitoring of the control history can lead to a compensator that can improve the closed-loop control performance under communication outages considerably

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38

MacKay, Maria Ellen. "Model based predictive control of nonlinear and multivariable systems." Thesis, Manchester Metropolitan University, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.337269.

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39

Baldivieso-Monasterios, Pablo Rodolfo. "Distributed model predictive control for reconfigurable large-scale systems." Thesis, University of Sheffield, 2018. http://etheses.whiterose.ac.uk/21527/.

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Large-scale Systems are gaining more importance in the modern world requiring flexible techniques capable of handling interactions. This thesis is concerned with the development of suitable algorithms based on Model Predictive Control (MPC) that guarantee stability, recursive feasibility and constraint satisfaction. In the first part of this thesis, the main properties and control challenges for controlling an Large-Scale System are brought together, and the main distributed approaches for solving these problems are surveyed. Also, two novel Distributed MPC algorithms are presented. A non-cent

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40

KarslÄ±gil, Orhan I. (Orhan Ismet) 1972. "Multiscale modeling and model predictive control of processing systems." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8995.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2000.<br>Includes bibliographical references.<br>Traditional approaches in Model Predictive Control (MPC) suffer from several weaknesses such as: (a) Satisfying the output constraints over a finite control horizon and guaranteeing closed loop stability. (b) The need for infinite horizon for robust stability and performance. (c) Limited representation of plant-model mismatch. (d) Inability to shape frequency response characteristics of the outputs through systematically selected weights in the objective functi

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41

Herceg, Domagoj. "Stochastic model predictive control of nonlinear and uncertain systems." Thesis, IMT Alti Studi Lucca, 2020. http://e-theses.imtlucca.it/309/1/Herceg_phdthesis.pdf.

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This thesis attempts to shed some additional light on pressing questions regarding the control of uncertain systems. Special focus is given to systems with uncertain uncertainty (inexactly known distribution), numerical optimization methods to enable the use of proposed advanced optimization methods in practice and systems controlled by an economic controller where stability is not always the primary objective. Current state-of-the-art methods often neglect that underlying uncertainty in a stochastic model is, in fact, uncertain as well in the sense that its probability distribution f

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42

Zhang, Yi-Ming. "Synthesis of state estimation and H∞ predictive control for networked control systems." Rouen, 2014. http://www.theses.fr/2014ROUES017.

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Cette thèse traite principalement du contrôle des systèmes en réseau. Ces derniers présentent des désagréments relatifs aux paquets d’information transportés, tels que les retards induits par le réseau, des ordres d’arrivée aléatoires voire des pertes potentielles de paquets, que ce soit dans la chaîne directe et/ou dans la chaîne de retour. La contribution de cette thèse est double : il s’agit (i) de synthétiser une loi de commande et (ii) d’élaborer un algorithme d'estimation robuste palliant tous deux à ces problèmes. Une commande prédictive généralisée basée sur l’état du système est ainsi

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43

Zhu, Yongjie. "Constrained nonlinear model predictive control for vehicle regulation." Columbus, Ohio : Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1222177849.

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44

Brugnolli, Mateus Mussi. "Predictive adaptive cruise control in an embedded environment." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/3/3139/tde-24092018-151311/.

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The development of Advanced Driving Assistance Systems (ADAS) produces comfort and safety through the application of several control theories. One of these systems is the Adaptive Cruise Control (ACC). In this work, a distribution of two control loops of such system is developed for an embedded application to a vehicle. The vehicle model was estimated using the system identification theory. An outer loop control manages the radar data to compute a suitable cruise speed, and an inner loop control aims for the vehicle to reach the cruise speed given a desired performance. For the inner loop, it

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45

Gupta, Manish. "Robust Repetitive Model Predictive Control for Systems with Uncertain Period-Time." Thesis, Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/5219.

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Repetitive Model Predictive Control (RMPC) incorporates the idea of Repetitive Control (RC) into Model Predictive Control (MPC) to take full advantage of the constraint handling, multivariable control features of MPC in periodic processes. The RMPC achieves perfect asymptotic tracking/rejection in periodic processes, provided that the period length used in the control formulation matches the actual period of the reference/disturbance exactly. Even a small mismatch between the actual period of process and the controller period can deteriorate the RMPC performance significantly. The period misma

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46

Ladoiye, Jasmeet Singh. "Control of Surgical Robots with Time Delay using Model Predictive Control." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38256.

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Minimum invasive surgery is based on bilateral teleoperation in which surgeon interacts with the master side to the slave side that is located at a distance. The synchronization in between the two ends is through a communication channel. The primary objective in the telesurgery is the position and force tracking providing the surgeon with high fidelity. The presence of time delays in the communication channels makes the realization more difficult, and sometimes it may even destabilize the system. The work focuses on a design of the force control system by using Model Predictive Control to com

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47

Huzmezan, Mihai. "Theory and aerospace applications of constrained model based predictive control." Thesis, University of Cambridge, 1998. https://www.repository.cam.ac.uk/handle/1810/272419.

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48

Zhang, Kun. "Computationally Aware Control of Cyber-Physical Systems: A Hybrid Model Predictive Control Approach." Diss., The University of Arizona, 2015. http://hdl.handle.net/10150/577315.

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Cyber-Physical Systems (CPS) are systems of collaborating computational elements controlling physical entities via communication. Such systems involve control processes of physical entities and computational processes. The control complexities originated from the physical dynamics and systematic constraints are difficult for traditional control approaches (e.g., PID control) to handle without an exponential increase in design/test etc. costs. Model predictive control (MPC) predicts and produces optimized control inputs based on its predictive model according to a cost function under given cons

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49

Dunn, John. "An investigation into neural network assisted model predictive control for nonlinear systems." Thesis, Brunel University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367442.

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50

Bulut, Baris. "Predictive control techniques with application to a hot strip finishing mill." Thesis, University of Strathclyde, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273379.

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