Controlo ótimo fracionário e aplicações biológicas

In this PhD thesis, we derive a Pontryagin Maximum Principle (PMP) for fractional optimal control problems and analyze a fractional mathematical model of COVID– 19 transmission dynamics. Fractional optimal control problems consist on optimizing a performance index functional subject to a fractional control system. One of the most important results in optimal control is the Pontryagin Maximum Principle, which gives a necessary optimality condition that every solution to the optimization problem must verify. First, we study properties of optimality for a dynamical system described by distributed-order non-local derivatives associated to a Lagrangian cost functional. We start by proving continuity and differentiability of solutions due to control perturbations. For smooth and unconstrained data, we obtain a weak version of Pontryagin's Maximum principle and a sufficient optimality condition under appropriate convexity. However, for controls taking values on a closed set, we use needle like variations to prove a strong version of Pontryagin's maximum principle. In the second part of the thesis, optimal control problems for fractional operators involving general analytic kernels are studied. We prove an integration by parts formula and a Gronwall inequality for fractional derivatives with a general analytic kernel. Based on these results, we show continuity and differentiability of solutions due to control perturbations leading to a weak version of the maximum principle. In addition, a wide class of combined fractional operators with general analytic kernels is considered. For this later problem, the control set is a closed convex subset of L2. Thus, using techniques from variational analysis, optimality conditions of Pontryagin type are obtained. Lastly, a fractional model for the COVID--19 pandemic, describing the realities of Portugal, Spain and Galicia, is studied. We show that the model is mathematically and biologically well posed. Then, we obtain a result on the global stability of the disease free equilibrium point. At the end we perform numerical simulations in order to illustrate the stability and convergence to the equilibrium point. For the data of Wuhan, Galicia, Spain, and Portugal, the order of the Caputo fractional derivative in consideration takes different values, characteristic of each region, which are not close to one, showing the relevance of the considered fractional models. 2020 Mathematics Subject Classification: 26A33, 49K15, 34A08, 34D23, 92D30.Nesta tese, derivamos o Princípio do Máximo de Pontryagin (PMP) para problemas de controlo ótimo fracionário e analisamos um modelo matemático fracionário para a dinâmica de transmissão da COVID-19. Os problemas de controlo ótimo fracionário consistem em otimizar uma funcional de índice de desempenho sujeita a um sistema de controlo fracionário. Um dos resultados mais importantes no controlo ótimo é o Princípio do Máximo de Pontryagin, que fornece uma condição de otimalidade necessária que toda a solução para o problema de otimização deve verificar. Primeiramente, estudamos propriedades de otimalidade para sistemas dinâmicos descritos por derivadas não-locais de ordem distribuída associadas a uma funcional de custo Lagrangiana. Começamos demonstrando a continuidade e a diferenciabilidade das soluções usando perturbações do controlo. Para dados suaves e sem restrições, obtemos uma versão fraca do princípio do Máximo de Pontryagin e uma condição de otimalidade suficiente sob convexidade apropriada. No entanto, para controlos que tomam valores num conjunto fechado, usamos variações do tipo agulha para provar uma versão forte do princípio do máximo de Pontryagin. Na segunda parte da tese, estudamos problemas de controlo ótimo para operadores fracionários envolvendo um núcleo analítico geral. Demonstramos uma fórmula de integração por partes e uma desigualdade Gronwall para derivadas fracionárias com um núcleo analítico geral. Com base nesses resultados, mostramos a continuidade e a diferenciabilidade das soluções por perturbações do controlo, levando a uma formulação de uma versão fraca do princípio do máximo de Pontryagin. Além disso, consideramos uma classe ampla de operadores fracionários combinados com núcleo analítico geral. Para este último problema, o conjunto de controlos é um subconjunto convexo fechado de L2. Assim, usando técnicas da análise variacional, obtemos condições de otimalidade do tipo de Pontryagin. Finalmente, estudamos um modelo fracionário da pandemia de COVID-19, descrevendo as realidades de Portugal, Espanha e Galiza. Mostramos que o modelo proposto é matematicamente e biologicamente bem colocado. Então, obtemos um resultado sobre a estabilidade global do ponto de equilíbrio livre de doença. No final, realizamos simulações numéricas para ilustrar a estabilidade e convergência do ponto de equilíbrio. Para os dados de Wuhan, Galiza, Espanha e Portugal, a ordem da derivada fracionária de Caputo em consideração toma valores diferentes característicos de cada região, e não próximos de um, mostrando a relevância de se considerarem modelos fracionários.Programa Doutoral em Matemática Aplicad

A survey on fuzzy fractional differential and optimal control nonlocal evolution equations

We survey some representative results on fuzzy fractional differential equations, controllability, approximate controllability, optimal control, and optimal feedback control for several different kinds of fractional evolution equations. Optimality and relaxation of multiple control problems, described by nonlinear fractional differential equations with nonlocal control conditions in Banach spaces, are considered.Comment: This is a preprint of a paper whose final and definite form is with 'Journal of Computational and Applied Mathematics', ISSN: 0377-0427. Submitted 17-July-2017; Revised 18-Sept-2017; Accepted for publication 20-Sept-2017. arXiv admin note: text overlap with arXiv:1504.0515

Optimal leader-following consensus of fractional opinion formation models

This paper deals with a control strategy enforcing consensus in a fractional opinion formation model with leadership, where the interaction rates between followers and the influence rate of the leader are functions of deviations of opinions between agents. The fractional-order derivative determines the impact of the memory during the opinion evolution. The problem of leader-following consensus control is cast in the framework of nonlinear optimal control theory. We study a finite horizon optimal control problem, in which deviations of opinions between agents and with respect to the leader are penalized along with the control that is applied only to the leader. The existence conditions for optimal consensus control are proved and necessary optimality conditions for the considered problem are derived. The results of the paper are illustrated by some examples.publishe

Fractional model of cancer immunotherapy and its optimal control

Cancer is one of the most serious illnesses in all of the world. Although most of the cancer patients are treated with chemotherapy, radiotherapy and surgery, wide research is conducted related to experimental and theoretical immunology. In recent years, the research on cancer immunotherapy has led to major medical advances. Cancer immunotherapy refers to the stimulation of immune system to deal with cancer cells. In medical practice, it is mainly achieved by using effector cells such as activated T-cells and Interleukin-2 (IL-2), which is the main cytokine responsible for lymphocyte activation, growth and differentiation. A well-known mathematical model, named as Kirschner-Panetta (KP) model, represents richly the dynamics of the interaction between cancer cells, IL-2 and the effector cells. The dynamics of the KP model is described and the solution to which is approximated by using polynomial approximation based methods such as Adomian decomposition method and differential transform method. The rich nonlinearity of the KP model causes these approaches to become so complicated in order to deal with the representation of polynomial approximations. It is illustrated that the approximated polynomials are in good agreement with the solution obtained by common numerical approaches. In the KP model, the growth of the tumour cells can be expressed by a linear function or any limited-growth function such as logistic equation, in which the cancer population possesses an upper bound mentioned as carrying capacity. Effector cells and IL-2 construct two external sources of medical treatment to stimulate immune system to eradicate cancer cells. Since the main goal in immunotherapy is to remove the tumour cells with the least probable medication side effects, an advanced version of the model may include a time dependent external sources of medical treatment, meaning that the external sources of medical treatment could be considered as control functions of time and therefore the optimum use of medical sources can be evaluated in order to achieve the optimal measure of an objective function. With this sense of direction, two distinct strategies are explored. The first one is to only consider the external source of effector cells as the control function to formulate an optimal control problem. It is shown under which circumstances, the tumour is eliminated. The approach in the formulation of the optimal control is the Pontryagin maximum principal. Furthermore the optimal control problem will be dealt with using particle swarm optimization (PSO). It is shown that the obtained results are significantly better than those obtained by previous researchers. The second strategy is to formulate an optimal control problem by considering both the two external sources as the controls. To our knowledge, it is the first time to present a multiple therapeutic protocol for the KP model. Some MATLAB routines are develop to solve the optimal control problems based on Pontryagin maximum principal and also the PSO. As known, fractional differential equations are more appropriate to describe the persistent memory of physical phenomena. Thus, the fractional KP model is defined in the sense of Caputo differentiation operator. An effective method for numerical treatment of the model is described, namely Predictor-Corrector method of Adams-Bashforth-Moulton type. A robust MATLAB routine is coded based on the mentioned approach and the solution obtained will be compared with those of the classical KP model. The code is prepared in such a way to be able to deal with systems of fractional differential equations, in which each equation has its own fractional order (i.e. multi-order systems of fractional differential equations). The theorems for existence of solutions and the stability analysis of the fractional KP model are represented. In this regard, a frequently used method of solving fractional differential equations (FDEs) is described in details, namely multi-step generalized differential transform method (MSGDTM), then it is illustrated that the method neglects the persistent memory property and takes the incorrect approach in dealing with numerical solutions of FDEs and therefore it is unfit to be used in differential equations governed by fractional differentiation operators. The sigmoidal behavior of the solution to the logistic equation caused it to be one of the most versatile models in natural sciences and therefore the fractional logistic equation would be a relevant problem to be dealt with. Thus, a power series of Mittag-Leffer functions is introduced, the behaviour of which is in good agreement with the solution to fractional logistic equation (FLE), and then a fractional integro-differential equation is represented and proved to be satisfied with the power series of Mittag-Leffler function. The obtained fractional integro-differential equation is named as modified fractional differential equation (MFDL) and possesses a nonlinear additive term related to the solution of the logistic equation (LE). The method utilized in the thesis, may be appropriately applied to the analysis of solutions to nonlinear fractional differential equations of mathematical physics. Inverse problems to FDEs occur in many branches of science. Such problems have been investigated, for instance, in fractional diffusion equation and inverse boundary value problem for semi- linear fractional telegraph equation. The determination of the order of fractional differential equations is an issue, which has been analyzed and discussed in, for instance, fractional diffusion equations. Thus, fractional order estimation has been conducted for some classes of linear fractional differential equations, by introducing the relationship between the fractional order and the asymptotic behaviour of the solutions to linear fractional differential equations. Fractional optimal control problems, in which the system and (or) the objective function are described based on fractional derivatives, are much more complicated to be solved by using a robust and reliable numerical approach. Thus, a MATLAB routine is provided to solve the optimal control for fractional KP model and the obtained solutions are compared with those of classical KP model. It is shown that the results for fractional optimal control problems are better than classical optimal control problem in the sense of the amount of drug administration

Contributions au calcul des variations et au principe du maximum de Pontryagin en calculs time scale et fractionnaire

Cette thèse est une contribution au calcul des variations et à la théorie du contrôle optimal dans les cadres discret, plus généralement time scale, et fractionnaire. Ces deux domaines ont récemment connu un développement considérable dû pour l un à son application en informatique et pour l autre à son essor dans des problèmes physiques de diffusion anormale. Que ce soit dans le cadre time scale ou dans le cadre fractionnaire, nos objectifs sont de : a) développer un calcul des variations et étendre quelques résultats classiques (voir plus bas); b) établir un principe du maximum de Pontryagin (PMP en abrégé) pour des problèmes de contrôle optimal. Dans ce but, nous généralisons plusieurs méthodes variationnelles usuelles, allant du simple calcul des variations au principe variationnel d Ekeland (couplé avec la technique des variations-aiguilles), en passant par l étude d invariances variationnelles par des groupes de transformations. Les démonstrations des PMPs nous amènent également à employer des théorèmes de point fixe et à prendre en considération la technique des multiplicateurs de Lagrange ou encore une méthode basée sur un théorème d inversion locale conique. Ce manuscrit est donc composé de deux parties : la Partie 1 traite de problèmes variationnels posés sur time scale et la Partie 2 est consacrée à leurs pendants fractionnaires. Dans chacune de ces deux parties, nous suivons l organisation suivante : 1. détermination de l équation d Euler-Lagrange caractérisant les points critiques d une fonctionnelle Lagrangienne ; 2. énoncé d un théorème de type Noether assurant l existence d une constante de mouvement pour les équations d Euler-Lagrange admettant une symétrie ; 3. énoncé d un théorème de type Tonelli assurant l existence d un minimiseur pour une fonctionnelle Lagrangienne et donc, par la même occasion, d une solution pour l équation d Euler-Lagrange associée (uniquement en Partie 2) ; 4. énoncé d un PMP (version forte en Partie 1, version faible en Partie 2) donnant une condition nécessaire pour les trajectoires qui sont solutions de problèmes de contrôle optimal généraux non-linéaires ; 5. détermination d une condition de type Helmholtz caractérisant les équations provenant d un calcul des variations (uniquement en Partie 1 et uniquement dans les cas purement continu et purement discret). Des théorèmes de type Cauchy-Lipschitz nécessaires à l étude de problèmes de contrôle optimal sont démontrés en Annexe.This dissertation deals with the mathematical fields called calculus of variations and optimal control theory. More precisely, we develop some aspects of these two domains in discrete, more generally time scale, and fractional frameworks. Indeed, these two settings have recently experience a significant development due to its applications in computing for the first one and to its emergence in physical contexts of anomalous diffusion for the second one. In both frameworks, our goals are: a) to develop a calculus of variations and extend some classical results (see below); b) to state a Pontryagin maximum principle (denoted in short PMP) for optimal control problems. Towards these purposes, we generalize several classical variational methods, including the Ekeland s variational principle (combined with needle-like variations) as well as variational invariances via the action of groups of transformations. Furthermore, the investigations for PMPs lead us to use fixed point theorems and to consider the Lagrange multiplier technique and a method based on a conic implicit function theorem. This manuscript is made up of two parts : Part A deals with variational problems on time scale and Part B is devoted to their fractional analogues. In each of these parts, we follow (with minor differences) the following organization: 1. obtaining of an Euler-Lagrange equation characterizing the critical points of a Lagrangian functional; 2. statement of a Noether-type theorem ensuring the existence of a constant of motion for Euler-Lagrange equations admitting a symmetry;3. statement of a Tonelli-type theorem ensuring the existence of a minimizer for a Lagrangian functional and, consequently, of a solution for the corresponding Euler-Lagrange equation (only in Part B); 4. statement of a PMP (strong version in Part A and weak version in Part B) giving a necessary condition for the solutions of general nonlinear optimal control problems; 5. obtaining of a Helmholtz condition characterizing the equations deriving from a calculus of variations (only in Part A and only in the purely continuous and purely discrete cases). Some Picard-Lindelöf type theorems necessary for the analysis of optimal control problems are obtained in Appendices.PAU-BU Sciences (644452103) / SudocSudocFranceF

Approximate controllability of Sobolev type fractional stochastic nonlocal nonlinear differential equations in Hilbert spaces

We introduce a new notion called fractional stochastic nonlocal condition, and then we study approximate controllability of class of fractional stochastic nonlinear differential equations of Sobolev type in Hilbert spaces. We use Hölder's inequality, fixed point technique, fractional calculus, stochastic analysis and methods adopted directly from deterministic control problems for the main results. A new set of sufficient conditions is formulated and proved for the fractional stochastic control system to be approximately controllable. An example is given to illustrate the abstract results