The aim of this thesis is to study a class of left-invariant optimal control problems on the matrix Lie group SE(2). We classify, under detached feedback equivalence, all controllable (left-invariant) control affine systems on SE(2). This result produces six types of control affine systems on SE(2). Hence, we study six associated left-invariant optimal control problems on SE(2). A left-invariant optimal control problem consists of minimizing a cost functional over the trajectory-control pairs of a left-invariant control system subject to appropriate boundary conditions. Each control problem is lifted from SE(2) to T*SE(2) ≅ SE(2) x se (2)*and then reduced to a problem on se (2)*. The maximum principle is used to obtain the optimal control and Hamiltonian corresponding to the normal extremals. Then we derive the (reduced) extremal equations on se (2)*. These equations are explicitly integrated by trigonometric and Jacobi elliptic functions. Finally, we fully classify, under Lyapunov stability, the equilibrium states of the normal extremal equations for each of the six types under consideration.

Uruguay is a pioneer in the use of renewable sources of energy and can usually satisfy its total demand from renewable sources. Control and optimization of the system is complicated by half of the installed power - wind and solar sources - be- ing non-controllable with high uncertainty and variability. In this work we present a novel optimization technique for efficient use of the production facilities. The dy- namical system is stochastic, and we deal with its non-Markovian dynamics through a Lagrangian relaxation. Continuous-time optimal control and value function are found from the solution to a sequence of Hamilton-Jacobi-Bellman partial differential equations associated with the system. We introduce a monotone scheme to avoid spurious oscillations in the numerical solution and apply the technique to a number of examples taken from the Uruguayan grid. We use parallelization and change of variables to reduce the computational times. Finally, we study the usefulness of extra system storage capacity offered by batteries.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第22488号 / 農博第2392号 / 新制||農||1076(附属図書館) / 学位論文||R2||N5268(農学部図書室) / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 藤原 正幸, 教授 村上 章, 准教授 宇波 耕一 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

This thesis considers classical methods to solve stochastic control problems and valuation problems from financial mathematics numerically. To this end, (linear) partial differential equations (PDEs) in non-divergence form or the optimality conditions known as the (nonlinear) Hamilton-Jacobi-Bellman (HJB) equations are solved by means of finite differences, volumes and elements. We consider all of these three approaches in detail after a thorough introduction to stochastic control problems and discuss various solution terms including classical solutions, strong solutions, weak solutions and viscosity solutions. A particular role in this thesis play degenerate problems. Here, a new model for the optimal control of an energy storage facility is developed which extends the model introduced in [Chen, Forsyth (2007)]. This four-dimensional HJB equation is solved by the classical finite difference Kushner-Dupuis scheme [Kushner, Dupuis (2001)] and a semi-Lagrangian variant which are both discussed in detail. Additionally, a convergence proof of the standard scheme in the setting of parabolic HJB equations is given. Finite volume schemes are another classical method to solve partial differential equations numerically. Sharing similarities to both finite difference and finite element schemes we develop a vertex-centered dual finite volume scheme. We discuss convergence properties and apply the scheme to the solution of HJB equations, which has not been done in such a broad context, to the best of our knowledge. Astonishingly, this is one of the first times the finite volume approach is systematically discussed for the solution of HJB equations. Furthermore, we give many examples which show advantages and disadvantages of the approach. Finally, we investigate novel tailored non-conforming finite element approximations of second-order PDEs in non-divergence form, utilizing finite-element Hessian recovery strategies to approximate second derivatives in the equation. We study approximations with both continuous and discontinuous trial functions. Of particular interest are a-priori and a-posteriori error estimates as well as adaptive finite element methods. In numerical experiments our method is compared with other approaches known from the literature. We discuss implementations of all three approaches in MATLAB (finite differences and volumes) and FEniCS (finite elements) publicly available in GitHub repositories under https://github.com/janblechschmidt. Many numerical experiments show convergence properties as well as pros and cons of the respective approach. Additionally, a new postprocessing procedure for policies obtained from numerical solutions of HJB equations is developed which improves the accuracy of control laws and their incurred values.

京都大学 / 0048 / 新制・課程博士 / 博士(農学) / 甲第20006号 / 農博第2190号 / 新制||農||1045(附属図書館) / 学位論文||H28||N5015(農学部図書室) / 33102 / 京都大学大学院農学研究科地域環境科学専攻 / (主査)教授 藤原 正幸, 教授 村上 章, 准教授 宇波 耕一 / 学位規則第4条第1項該当 / Doctor of Agricultural Science / Kyoto University / DFAM

Merton’s Optimal Investment-Consumption Problem is a classic optimization problem in finance. It aims to find the optimal controls for a portfolio with both risky and risk-less assets, inorder to maximize an investor’s utility function. One of the controls is the optimal allocationof wealth invested in a risky asset and the other control is the consumption rate. The problemis solved by using Dynamic Programming and the related Hamilton-Jacobi-Bellman equation.One of the disadvantages of the original problem is the consideration of constant volatility. Inthis thesis, we extend Merton’s problem considering the Grzelak-Oosterlee-Van Veeren modelthat describes the dynamics of a risky asset with stochastic volatility and stochastic interestrate. We derive the related Hamilton-Jacobi-Bellman for Merton’s problem considering theGrzelak-Oosterlee-Van Veeren model. We simulate the controls from Merton’s problem intwo different cases, one case where the volatility and interest rate are stochastic, following theGOVV-model. In the other case, the volatility and interest rate are assumed to be constant, asin Merton’s problem. The results obtained from simulations show that the case with stochasticvolatility and interest gave the same results as the case where the volatility and the interest ratewere assumed to be constant.

This thesis concerns the approximation of optimally controlled partial differential equations for applications in optimal design and reconstruction. Such optimal control problems are often ill-posed and need to be regularized to obtain good approximations. We here use the theory of the corresponding Hamilton-Jacobi-Bellman equations to construct regularizations and derive error estimates for optimal design problems. The constructed Pontryagin method is a simple and general method where the first, analytical, step is to regularize the Hamiltonian. Next its stationary Hamiltonian system, a nonlinear partial differential equation, is computed efficiently with the Newton method using a sparse Jacobian. An error estimate for the difference between exact and approximate objective functions is derived, depending only on the difference of the Hamiltonian and its finite dimensional regularization along the solution path and its L2 projection, i.e. not on the difference of the exact and approximate solutions to the Hamiltonian systems. In the thesis we present solutions to applications such as optimal design and reconstruction of conducting materials and elastic structures. / QC 20101110

L'objectif de cette thèse est de développer la théorie du contrôle stochastique et ses applications en dynamique des populations. D'un point de vue théorique, nous présentons l'étude de problèmes de contrôle stochastique à horizon fini sur des processus de diffusion, de branchement non linéaire et de branchement-diffusion. Dans chacun des cas, nous raisonnons par la méthode de la programmation dynamique en veillant à démontrer soigneusement un argument de conditionnement analogue à la propriété de Markov forte pour les processus contrôlés. Le principe de la programmation dynamique nous permet alors de prouver que la fonction valeur est solution (régulière ou de viscosité) de l'équation de Hamilton-Jacobi-Bellman correspondante. Dans le cas régulier, nous identifions également un contrôle optimal markovien par un théorème de vérification. Du point de vue des applications, nous nous intéressons à la modélisation mathématique du cancer et de ses stratégies thérapeutiques. Plus précisément, nous construisons un modèle hybride de croissance de tumeur qui rend compte du rôle fondamental de l'acidité dans l'évolution de la maladie. Les cibles de la thérapie apparaissent explicitement comme paramètres du modèle afin de pouvoir l'utiliser comme support d'évaluation de stratégies thérapeutiques. / The main objective of this thesis is to develop stochastic control theory and applications to population dynamics. From a theoritical point of view, we study finite horizon stochastic control problems on diffusion processes, nonlinear branching processes and branching diffusion processes. In each case we establish a dynamic programmic principle by carefully proving a conditioning argument similar to the strong Markov property for controlled processes. Then we deduce that the value function is a (viscosity or regular) solution of the associated Hamilton-Jacobi-Bellman equation. In the regular case, we further identify an optimal control in the class of markovian strategies thanks to a verification theorem. From a pratical point of view, we are interested in mathematical modelling of cancer growth and treatment. More precisely, we build a hybrid model of tumor growth taking into account the essential role of acidity. Therapeutic targets appear explicitly as model parameters in order to be able to evaluate treatment strategies.

La simulation numérique est indissociable du calcul haute performance. Ces vingt dernières années,l'informatique a connu l'émergence d'architectures parallèles multi-niveaux. Exploiter efficacement lapuissance de calcul de ces machines peut s'avérer être une tâche délicate et requérir une expertise à la foistechnologique sur des notions avancées de parallélisme ainsi que scientifique de part la nature même desproblèmes traités.Le travail de cette thèse est pluri-disciplinaire s'appuyant sur la conception d'une librairie de calculparallèle réutilisable pour la résolution des équations Hamilton-Jacobi-Bellman. Ces équations peuventse retrouver dans des domaines diverses et variés tels qu'en biomédical, géophysique, ou encore robotiqueen l'occurence sur les applications de planification de mouvement et de reconstruction de formestri-dimensionnelles à partir d'images bi-dimensionnelles. Nous montrons que les principaux algorithmesnumériques amenant a résoudre ces équations telles que les méthodes de type fast marching, ne sont pasappropriés pour être efficaces dans un contexte parallèle. Nous proposons la méthode buffered fast iterativequi permet d'obtenir une scalabilité parallèle non obtenue jusqu'alors. Un des points sensibles relevésdans cette thèse est de parvenir à trouver une recette de compromis entre abstraction, performance etmaintenabilité afin de garantir non seulement une réutilisabilitédans le sens classique du domaine de génielogiciel mais également en terme de réutilisabilité séquentielle/parallèle / Numerical simulation is strongly bound with high performance computing. Programming scientificsoftwares requires at the same time good knowledge on the mathematical numerical models and alsoon the techniques to make them efficient on today's computers. Indeed, these last twenty years, wehave experienced the rising of multi-level parallel architectures. The work in this thesis dissertation ismultidisciplinary by designing a reusable parallel numerical library for solving Hamilton-Jacobi-Bellmanequations. Such equations are involved in various fields such as in biomedical, geophysics or robotics. Inparticular, we will show interests in path planning and shape from shading applications. We show thatthe methods to solve these equations such as the widely used fast marching method, are not designedto be used effciently in a parallel context. We propose a buffered fast iterative method which givesan interesting parallel scalability. This dissertation takes interest in the challenge to find compromisesbetween abstraction, performance and maintainability in order to combine both software reusability andalso sequential/parallel reusability. We propose code abstraction allowing algorithmic and data genericitywhile trying to keep a maintainable and performant code potentially parallelizable

Cette thèse étudie des modèles mathématiques inspirés par la biologie. Plus précisément, nous nous concentrons sur des équations aux dérivées partielles cinétiques. Les champs d'application des équations cinétiques sont nombreux mais nous nous concentrons ici sur des phénomènes de propagation d'espèces invasives, notamment la bactérie Escherichia coli et le crapaud buffle Rhinella marina.La première partie de la thèse ne présente pas de résultats mathématiques. Nous construisons plusieurs modélisations pour la dispersion à grande échelle du crapaud buffle en Australie. Nous confrontons ces mêmes modèles à des données statistiques multiples (taux de fécondité, taux de survie, comportements dispersifs) pour mesurer leur pertinence. Ces modèles font intervenir des processus à sauts de vitesses et des équations cinétiques.Dans la seconde partie, nous étudions des phénomènes de propagation dans des modèles cinétiques plus simples. Nous illustrons plusieurs méthodes pour établir mathématiquement des formules de vitesse de propagation dans ces modèles. Cette partie nous amène à établir des résultats de convergence d'équations cinétiques vers des équations de Hamilton-Jacobi par la méthode de la fonction test perturbée. Nous montrons également comment le formalisme Hamilton-Jacobi permet de trouver des résultats de propagation et enfin, nous construisons des solutions en ondes progressives pour un modèle de transport-réaction. Dans la dernière partie, nous établissons un résultat de limite de diffusion stochastique pour une équation cinétique aléatoire. Pour ce faire, nous adaptons la méthode de la fonction test perturbée sur la formulation d'une EDP stochastique en terme de générateurs infinitésimaux.La thèse comporte également une annexe qui expose les données trajectorielles des crapauds dont nous nous servons en première partie." / In this thesis, we study some biology inspired mathematical models. More precisely, we focus on kinetic partial differential equations. The fields of application of such equations are numerous but we focus here on propagation phenomena for invasive species, the Escherichia coli bacterium and the cane toad Rhinella marina, for example. The first part of this this does not establish any mathematical result. We build several models for the dispersion of the cane toad in Australia. We confront those very models to multiple statistical data (birth rate, survival rate, dispersal behaviors) to test their validity. Those models are based on velocity-jump processes and kinetic equations. In the second part, we study propagation phenomena on simpler kinetic models. We illustrate several methods to mathematically establish propagation speed in this models. This part leads us to establish convergence results of kinetic equations to Hamilton-Jacobi equations by the perturbed test function method. We also show how to use the Hamilton-Jacobi framework to establish spreading results et finally, we build travelling wave solutions for reaction-transport model. In the last part, we establish a stochastic diffusion limit result for a kinetic equation with a random term. To do so, we adapt the perturbed test function method on the formulation of a stochastic PDE in term of infinitesimal generators. The thesis also contains an annex which presents the data on toads’ trajectories used in the first part."