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Analytical and Numerical Optimal Motion Planning for an Underwater GliderKraus, Robert J. 06 May 2010 (has links)
The use of autonomous underwater vehicles (AUVs) for oceanic observation and research is becoming more common. Underwater gliders are a specific class of AUV that do not use conventional propulsion. Instead they change their buoyancy and center of mass location to control attitude and trajectory. The vehicles spend most of their time in long, steady glides, so even minor improvements in glide range can be magnified over multiple dives.
This dissertation presents a rigid-body dynamic system for a generic vehicle operating in a moving fluid (ocean current or wind). The model is then reduced to apply to underwater gliders. A reduced-order point-mass model is analyzed for optimal gliding in the presence of a current. Different numerical method solutions are compared while attempting to achieve maximum glide range. The result, although approximate, provides good insight into how the vehicles may be operated more effectively.
At the end of each dive, the gliders must change their buoyancy and pitch to transition to a climb. Improper scheduling of the buoyancy and pitch change may cause the vehicle to stall and lose directional stability. Optimal control theory is applied to the buoyancy and angle of attack scheduling of a point-mass model.
A rigid-body model is analyzed on a singular arc steady glide. An analytical solution for the control required to stay on the arc is calculated. The model is linearized to calculate possible perturbation directions while remaining on the arc. The nonlinear model is then propagated in forward and reverse time with the perturbations and analyzed. Lastly, one of the numerical solutions is analyzed using the singular arc equations for verification. This work received support from the Office of Naval Research under Grant Number N00014-08-1-0012. / Ph. D.
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Revisiting the Lucas ModelSkritek, Bernhard, Crespo Cuaresma, Jesus, Kryazhimskii, Arkadii V., Prettner, Klaus, Prskawetz, Alexia, Rovenskaya, Elena 09 1900 (has links) (PDF)
We revisit the influential economic growth model by Lucas (1988) ["On the mechanics of economic development." Journal of Monetary Economics, 22(1):3-42], assuming that households optimally allocate consumption and education over the life-cycle given an exogenous interest rate and exogenous wages. We show that in such a partial equilibrium setting, the original two-state (physical capital and human capital) optimization problem can be decomposed into two single-state optimal control models. This transformation allows us to rigorously prove the existence of a singular control describing the allocation of education time along a balanced growth path. We derive a constructive condition for a singular control to exist and show that under this condition infinitely many singular controls are optimal in the individual household problem. In contrast to the original general equilibrium framework in which an agent always chooses part-time education and part-time work, in our framework such an agent might find it optimal to allocate her whole available time to education at the beginning of her life and to focus on labor supply only when she is older. (authors' abstract) / Series: Department of Economics Working Paper Series
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The Importance of the Riemann-Hilbert Problem to Solve a Class of Optimal Control ProblemsDewaal, Nicholas 20 March 2007 (has links) (PDF)
Optimal control problems can in many cases become complicated and difficult to solve. One particular class of difficult control problems to solve are singular control problems. Standard methods for solving optimal control are discussed showing why those methods are difficult to apply to singular control problems. Then standard methods for solving singular control problems are discussed including why the standard methods can be difficult and often impossible to apply without having to resort to numerical techniques. Finally, an alternative method to solving a class of singular optimal control problems is given for a specific class of problems.
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Finite-time partial stability, stabilization, semistabilization, and optimal feedback controlL'afflitto, Andrea 08 June 2015 (has links)
Asymptotic stability is a key notion of system stability for controlled dynamical systems as it guarantees that the system trajectories are bounded in a neighborhood of a given isolated equilibrium point and converge to this equilibrium over the infinite horizon. In some applications, however, asymptotic stability is not the appropriate notion of stability. For example, for systems with a continuum of equilibria, every neighborhood of an equilibrium contains another equilibrium and a nonisolated equilibrium cannot be asymptotically stable. Alternatively, in stabilization of spacecraft dynamics via gimballed gyroscopes, it is desirable to find state- and output-feedback control laws that guarantee partial-state stability of the closed-loop system, that is, stability with respect to part of the system state. Furthermore, we may additionally require finite-time stability of the closed-loop system, that is, convergence of the system's trajectories to a Lyapunov stable equilibrium in finite time.
The Hamilton-Jacobi-Bellman optimal control framework provides necessary and sufficient conditions for the existence of state-feedback controllers that minimize a given performance measure and guarantee asymptotic stability of the closed-loop system. In this research, we provide extensions of the Hamilton-Jacobi-Bellman optimal control theory to develop state-feedback control laws that minimize nonlinear-nonquadratic performance criteria and guarantee semistability, partial-state stability, finite-time stability, and finite-time partial state stability of the closed-loop system.
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Pilotage des cycles limites dans les systèmes dynamiques hybrides : application aux alimentations électriques statiques / Limit cycle control in hybrid systems. Application in static power suppliesPatino, Diego 06 February 2009 (has links)
Cette thèse s'intéresse au pilotage des cycles limites pour une classe particulière de systèmes hybrides (SDH): les systèmes commutés cycliques. La thématique des SDH est née du constat d'insuffisance des modèles dynamiques classiques pour décrire les comportements lorsque des aspects évènementiels interviennent. Une classe particulièrement importante de SDH est formée par celle qui présente un régime permanent cyclique. Ces systèmes ont des points de fonctionnement non auto-maintenables: il n'existe pas de commande qui maintienne le système sur ce point. Le maintien n'est assuré qu'en valeur moyenne, en effectuant un cycle dans un voisinage du point par commutation des sous systèmes. L'établissement d'une loi de commutation pour cette classe de systèmes doit répondre aux objectifs de stabilité et de performance dynamique, mais doit également garantir la satisfaction de critères liés à la forme d'onde. A l'heure actuelle, peu de méthodes de commande prennent en compte le caractère cyclique du système. Les travaux de cette thèse ont pour objectif de développer des méthodes génériques et robustes pour piloter cette classe de systèmes. Les algorithmes proposés doivent également pouvoir être implémenté en temps réels. On modélise le système comme un système non - linéaire affine en la commande dont la loi de commande apparait dans le modèle. Ce type de modélisation permet d'envisager deux types de synthèse: l'une à base de commande prédictive et l'autre à base de commande optimale. Ce travail est validé par une partie applicative sur des manipulations dans le CRAN et dans des laboratoires du réseau d'excellence européenne HYCON dans le cadre duquel s'est déroulé cette étude / This work deals with limit cycle control for one particular class of hybrid dynamical systems (HDS): The cyclic switched systems. The HDS were born because the traditional dynamical models were not able to describe complex behaviors and most of all, behaviors with discontinuities. From an application point of view, one important class of HDS depicts a cyclic behavior in steady state. The main characteristic of these systems is that the operation point cannot be maintained: It does not exist a control that maintains the system on a desired operation point. However, this point can be obtained in average by turning into its neighborhood. Thus, a cycle is produced by switching among the system modes. A switched control law must satisfy stability and dynamic performance. Moreover, criteria related to the waveform must be verified. Nowadays, few methods take into account the cyclic behavior of the system. In this research, some generic methods are studied. They show good performance for controlling the cyclic switched systems. The proposed algorithms can be implemented in real-time. The approaches are based on an affine non-linear model of the system whose control explicitly appears. Two control methods are considered: i) A predictive control, ii) An optimal control. Since the predictive control is a good choice for tracking, it will be able to maintain the system in a cycle. The optimal control yields solutions that can be applied to the transients. Some experiments with both control methods applied to the power converters are shown. These tests were carried out not only in our laboratory (CRAN), but also in other laboratories as part of the HYCON excellence network
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Singular control of optional random measuresBank, Peter 14 December 2000 (has links)
In dieser Arbeit untersuchen wir das Problem der Maximierung bestimmter konkaver Funktionale auf dem Raum der optionalen, zufälligen Maße. Deartige Funktionale treten in der mikroökonomischen Literatur auf, wo ihre Maximierung auf die Bestimmung des optimalen Konsumplans eines ökomischen Agenten hinausläuft. Als Alternative zu den wohlbekannten Methoden der dynamischen Programmierung wird ein neuer Zugang vorgestellt, der es erlaubt, die Struktur der maximierenden Maße in einem über den üblicherweise angenommenen Markovschen Rahmen hinausgehenden, allgemeinen Semimartingalrahmen zu klären. Unser Zugang basiert auf einer unendlichdimensionalen Version des Kuhn-Tucker-Theorems. Die implizierten Bedingungen erster Ordnung erlauben es uns, das Maximierungsproblem auf ein neuartiges Darstellungsproblem für optionale Prozesse zu reduzieren, das damit als ein nicht-Markovsches Substitut für die Hamilton-Jacobi-Bellman Gleichung der dynamischen Programmierung dient. Um dieses Darstellungsproblem im deterministischen Fall zu lösen, führen wir eine zeitinhomogene Verallgemeinerung des Konvexitätsbegriffs ein. Die Lösung im allgemeinen stochastischen Fall ergibt sich über eine enge Beziehung zur Theorie des Gittins-Index der optimalen dynamischen Planung. Unter geeigneten Annahmen gelingt ihre Darstellung in geschlossener Form. Es zeigt sich dabei, daß die maximierenden Maße absolutstetig, diskret und auch singulär sein können, je nach Struktur der dem Problem zugrundeliegenden Stochastik. Im mikroökonomischen Kontext ist es natürlich, daß Problem in einen Gleichgewichtsrahmen einzubetten. Der letzte Teil der Arbeit liefert hierzu ein allgemeines Existenzresultat für ein solches Gleichgewicht. / In this thesis, we study the problem of maximizing certain concave functionals on the space of optional random measures. Such functionals arise in microeconomic theory where their maximization corresponds to finding the optimal consumption plan of some economic agent. As an alternative to the well-known methods of Dynamic Programming, we develop a new approach which allows us to clarify the structure of maximizing measures in a general stochastic setting extending beyond the usually required Markovian framework. Our approach is based on an infinite-dimensional version of the Kuhn-Tucker Theorem. The implied first-order conditions allow us to reduce the maximization problem to a new type of representation problem for optional processes which serves as a non-Markovian substitute for the Hamilton-Jacobi-Bellman equation of Dynamic Programming. In order to solve this representation problem in the deterministic case, we introduce a time-inhomogeneous generalization of convexity. The stochastic case is solved by using an intimate relation to the theory of Gittins-indices in optimal dynamic scheduling. Closed-form solutions are derived under appropriate conditions. Depending on the underlying stochastics, maximizing random measures can be absolutely continuous, discrete, and also singular. In the microeconomic context, it is natural to embed the above maximization problem in an equilibrium framework. In the last part of this thesis, we give a general existence result for such an equilibrium.
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Fenômeno Fuller em problemas de controle ótimo: trajetórias em tempo mínino de veículos autônomos subaquáticos / Fuller Phenomenon in optimal control problems: minimum time path of autonomous underwater vehicles.Eduardo Oda 03 June 2008 (has links)
As equações do modelo bidimensional de veículos autônomos subaquáticos fornecem um exemplo de sistema de controle não linear com o qual podemos ilustrar propriedades da teoria de controle ótimo. Apresentamos, sistematicamente, como os conceitos de formalismo hamiltoniano e teoria de Lie aparecem de forma natural neste contexto. Para tanto, estudamos brevemente o Princípio do Máximo de Pontryagin e discutimos características de sistemas afins. Tratamos com cuidado do Fenômeno Fuller, fornecendo critérios para decidir quando ele está ou não presente em junções, utilizando para isso uma linguagem algébrica. Apresentamos uma abordagem numérica para tratar problemas de controle ótimo e finalizamos com a aplicação dos resultados ao modelo bidimensional de veículo autônomo subaquático. / The equations of the two-dimensional model for autonomous underwater vehicles provide an example of a nonlinear control system which illustrates properties of optimal control theory. We present, systematically, how the concepts of the Hamiltonian formalism and the Lie theory naturally appear in this context. For this purpose, we briefly study the Pontryagin\'s Maximum Principle and discuss features of affine systems. We treat carefully the Fuller Phenomenon, providing criteria to detect its presence at junctions with an algebraic notation. We present a numerical approach to treat optimal control problems and we conclude with an application of the results in the bidimesional model of autonomous underwater vehicle.
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Fenômeno Fuller em problemas de controle ótimo: trajetórias em tempo mínino de veículos autônomos subaquáticos / Fuller Phenomenon in optimal control problems: minimum time path of autonomous underwater vehicles.Oda, Eduardo 03 June 2008 (has links)
As equações do modelo bidimensional de veículos autônomos subaquáticos fornecem um exemplo de sistema de controle não linear com o qual podemos ilustrar propriedades da teoria de controle ótimo. Apresentamos, sistematicamente, como os conceitos de formalismo hamiltoniano e teoria de Lie aparecem de forma natural neste contexto. Para tanto, estudamos brevemente o Princípio do Máximo de Pontryagin e discutimos características de sistemas afins. Tratamos com cuidado do Fenômeno Fuller, fornecendo critérios para decidir quando ele está ou não presente em junções, utilizando para isso uma linguagem algébrica. Apresentamos uma abordagem numérica para tratar problemas de controle ótimo e finalizamos com a aplicação dos resultados ao modelo bidimensional de veículo autônomo subaquático. / The equations of the two-dimensional model for autonomous underwater vehicles provide an example of a nonlinear control system which illustrates properties of optimal control theory. We present, systematically, how the concepts of the Hamiltonian formalism and the Lie theory naturally appear in this context. For this purpose, we briefly study the Pontryagin\'s Maximum Principle and discuss features of affine systems. We treat carefully the Fuller Phenomenon, providing criteria to detect its presence at junctions with an algebraic notation. We present a numerical approach to treat optimal control problems and we conclude with an application of the results in the bidimesional model of autonomous underwater vehicle.
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Maximum Principle for Reflected BSPDE and Mean Field Game Theory with ApplicationsFu, Guanxing 29 June 2018 (has links)
Diese Arbeit behandelt zwei Gebiete: stochastische partielle Rückwerts-Differentialgleichungen (BSPDEs) und Mean-Field-Games (MFGs).
Im ersten Teil wird über eine stochastische Variante der De Giorgischen Iteration ein Maximumprinzip für quasilineare reflektierte BSPDEs (RBSPDEs) auf allgemeinen Gebieten bewiesen. Als Folgerung erhalten wir ein Maximumprinzip für RBSPDEs auf beschränkten, sowie für BSPDEs auf allgemeinen Gebieten. Abschließend wird das lokale Verhalten schwacher Lösungen untersucht.
Im zweiten Teil zeigen wir zunächst die Existenz von Gleichgewichten in MFGs mit singulärer Kontrolle. Wir beweisen, dass die Lösung eines MFG ohne Endkosten und ohne Kosten in der singulären Kontrolle durch die Lösungen eines MFGs mit strikt regulären Kontrollen approximiert werden kann. Die vorgelegten Existenz- und Approximationsresultat basieren entscheidend auf der Wahl der Storokhod M1 Topologie auf dem Raum der Càdlàg-Funktion.
Anschließend betrachten wir ein MFG optimaler Portfolioliquidierung unter asymmetrischer Information. Die Lösung des MFG charakterisieren wir über eine stochastische Vorwärts-Rückwärts-Differentialgleichung (FBSDE) mit singulärer Endbedingung der Rückwärtsgleichung oder alternativ über eine FBSDE mit endlicher Endbedingung, jedoch singulärem Treiber. Wir geben ein Fixpunktargument, um die Existenz und Eindeutigkeit einer Kurzzeitlösung in einem gewichteten Funktionenraum zu zeigen. Dies ermöglicht es, das ursprüngliche MFG mit entsprechenden MFGs ohne Zustandsendbedinung zu approximieren.
Der zweite Teil wird abgeschlossen mit einem Leader-Follower-MFG mit Zustandsendbedingung im Kontext optimaler Portfolioliquidierung bei hierarchischer
Agentenstruktur. Wir zeigen, dass das Problem beider Spielertypen auf singuläre FBSDEs zurückgeführt werden kann, welche mit ähnlichen Methoden wie im vorangegangen Abschnitt behandelt werden können. / The thesis is concerned with two topics: backward stochastic partial differential equations and mean filed games.
In the first part, we establish a maximum principle for quasi-linear reflected backward stochastic partial differential equations (RBSPDEs) on a general domain by using a stochastic version of De Giorgi’s iteration. The maximum principle for RBSPDEs on a bounded domain and the maximum principle for BSPDEs on a general domain are obtained as byproducts. Finally, the local behavior of the weak solutions is considered.
In the second part, we first establish the existence of equilibria to mean field games (MFGs) with singular controls. We also prove that the solutions to MFGs with no terminal cost and no cost from singular controls can be approximated by the solutions, respectively control rules, for MFGs with purely regular controls. Our existence and approximation results strongly hinge on the use of the Skorokhod M1 topology on the space of càdlàg functions.
Subsequently, we consider an MFG of optimal portfolio liquidation under asymmetric
information. We prove that the solution to the MFG can be characterized in terms of a forward backward stochastic differential equation (FBSDE) with possibly singular terminal condition on the backward component or, equivalently, in terms of an FBSDE with finite terminal value, yet singular driver. We apply the fixed point argument to prove the existence and uniqueness on a short time horizon in a weighted space. Our existence and uniqueness result allows to prove that our MFG can be approximated by a sequence of MFGs without state constraint.
The final result of the second part is a leader follower MFG with terminal constraint arising from optimal portfolio liquidation between hierarchical agents. We show the problems for both follower and leader reduce to the solvability of singular FBSDEs, which can be solved by a modified approach of the previous result.
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Optimal Trading with Multiplicative Transient Price Impact for Non-Stochastic or Stochastic LiquidityFrentrup, Peter 28 October 2019 (has links)
Diese Arbeit untersucht eine Reihe multiplikativer Preiseinflussmodelle für das Handeln in einer riskanten Anlage. Unser risikoneutraler Investor versucht seine zu erwartenden Handelserlöse zu maximieren. Zunächst modellieren wir den vorübergehende Preiseinfluss als deterministisches Funktional der Handelsstrategie. Wir stellen den Zusammenhang mit Limit-Orderbüchern her und besprechen die optimale Strategie zum Auf- bzw. Abbau einer Anlageposition bei a priori unbeschränkem Anlagehorizont. Anschließend lösen wir das Optimierungsproblem mit festem Anlagehorizon in zwei Schritten. Mittels Variationsrechnung lässt sich die freie Grenzefläche, die Kauf- und Verkaufsregionen trennt, als lokales Optimum identifizieren, was entscheidend für die Verifikation globaler Optimalität ist. Im zweiten Teil der Arbeit erweitern wir den zwischengeschalteten Markteinflussprozess um eine stochastische Komponente, wodurch optimale Strategien dynamisch an zufällige Liquiditätsschwankungen adaptieren. Wir bestimmen die optimale Liquidierungsstrategie im zeitunbeschränkten Fall als die reflektierende Lokalzeit, die den Markteinfluss unterhalb eines explizit beschriebenen nicht-konstanten Grenzlevels hält. Auch dieser Beweis kombiniert Variationsrechnung und direkten Methoden. Um nun eine Zeitbeschränkung zu ermöglichen, müssen wir Semimartingalstrategien zulassen. Skorochods M1-Toplogie ist der Schlüssel, um die Klasse der möglichen Strategien in einer umfangreichen Familie von Preiseinflussmodellen, welche sowohl additiven, als auch multiplikativen Preiseinfluss umfasst, mit deterministischer oder stochastischer Liquidität, eindeutig von endlichen Variations- auf allgemeine càdlàg Strategien zu erweitern. Nach Einführung proportionaler Transaktionskosten lösen wir das entsprechende eindimensionale freie Grenzproblem des optimalen unbeschränkten Handels und beleuchten mögliche Lösungsansätze für das Liquidierungsproblem, das mit dem Verkauf der letzten Anleihe endet. / In this thesis, we study a class of multiplicative price impact models for trading a single risky asset. We model price impact to be multiplicative so that prices are guaranteed to stay non-negative. Our risk-neutral large investor seeks to maximize expected gains from trading. We first introduce a basic variant of our model, wherein the transient impact is a deterministic functional of the trading strategy. We draw the connection to limit order books and give the optimal strategy to liquidate or acquire an asset position infinite time horizon. We then solve the optimization problem for finite time horizon two steps. Calculus of variations allows to identify the free boundary surface that separates buy and sell regions and moreover show its local optimality, which is a crucial ingredient for the verification giving (global) optimality. In the second part of the thesis, we add stochasticity to the auxiliary impact process. This causes optimal strategies to dynamically adapt to random changes in liquidity. We identify the optimal liquidation strategy in infinite horizon as the reflection local time which keeps the market impact process below an explicitly described non-constant free boundary level. Again the proof technique combines classical calculus of variations and direct methods. To now impose a time constraint, we need to admit semimartingale strategies. Skorokhod's M1 topology is key to uniquely extend the class of admissible controls from finite variation to general càdlàg strategies in a broad class of market models including multiplicative and additive price impact, with deterministic or stochastic liquidity. After introducing proportional transaction costs in our model, we solve the related one-dimensional free boundary problem of unconstrained optimal trading and highlight possible solution methods for the corresponding liquidation problem where trading stops as soon as all assets are sold.
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