Grâce aux avancées conjointes des systèmes microélectroniques, des technologies sans fil et de la microélectronique embarquée, les réseaux de capteurs sans fil (RCsF) ont récemment pu voir le jour. Très sophistiqués et en interaction directe avec leur environnement, ces systèmes informatiques et électroniques communiquent principalement à travers des réseaux radio qui en font des objets communicants autonomes. Ils offrent l'opportunité de prendre en compte les évolutions temporelles et spatiales du monde physique environnant. Les RCsF se retrouvent donc au cœur de nombreuses applications couvrant des domaines aussi variés que la santé, la domotique, l'intelligence ambiante, les transports, la sécurité, l'agronomie et l'environnement. Ils connaissent un véritable essor et ce dans divers domaines des STIC : hardware, système d'exploitation, conception d'antenne, système d'information, protocoles réseaux, théorie des graphes, algorithmique distribuée, sécurité, etc. L’intérêt des communautés issues de la recherche et de l’industrie pour ces RCsF s’est accru par la potentielle fiabilité, précision, flexibilité, faible coût ainsi que la facilité de déploiement de ces systèmes. La spontanéité, l’adaptabilité du réseau et la dynamicité de sa topologie dans le déploiement des RCsF soulèvent néanmoins de nombreuses questions encore ouvertes. Dans le cadre de cette thèse, nous nous sommes intéressés aux aspects liés à la problématique du routage dans un RCsF, l’objectif étant de proposer des approches algorithmiques permettant de faire du routage adaptatif multi critères dans un RCsF. Nous nous sommes concentrés sur deux critères principaux : la consommation d’énergie dans les capteurs et le délai d’acheminement des informations collectées par les capteurs. Nous avons proposé ainsi un nouveau protocole de routage, appelé EDEAR (Energy and Delay Efficient Adaptive Routing), qui se base sur un mécanisme d’apprentissage continu et distribué permettant de prendre en compte la dynamicité du réseau. Celui-ci utilise deux types d’agents explorateurs chargés de la collecte de l’information pour la mise à jour des tables de routage. Afin de réduire la consommation d’énergie et la surcharge du réseau, nous proposons également un processus d’exploration des routes basé sur une diffusion optimisée des messages de contrôle. Le protocole EDEAR calcule les routes qui minimisent simultanément l’énergie consommée et le délai d’acheminement des informations de bout en bout permettant ainsi de maximiser la durée de vie du réseau. L’apprentissage se faisant de manière continue, le routage se fait donc de façon évolutive et permet ainsi une réactivité aux différents évènements qui peuvent intervenir sur le réseau. Le protocole proposé est validé et comparé aux approches traditionnelles, son efficacité au niveau du routage adaptatif est mise particulièrement en évidence aussi bien dans le cas de capteurs fixes que de capteurs mobiles. En effet, celui-ci permet une meilleure prise en compte de l'état du réseau contrairement aux approches classiques / Through the joint advanced microelectronic systems, wireless technologies and embedded microelectronics, wireless sensor networks have recently been possible. Given the convergence of communications and the emergence of ubiquitous networks, sensor networks can be used in several applications and have a great impact on our everyday life. There is currently a real interest of research in wireless sensor networks; however, most of the existing routing protocols propose an optimization of energy consumption without taking into account other metrics of quality of service. In this thesis, we propose an adaptive routing protocol called "EDEAR" which takes into account both necessary criteria to the context of communications in sensor networks, which are energy and delay of data delivery. We are looking the routes for optimizing a nodes’ lifetime in the network, these paths are based on joint optimization of energy consumption and delay through a multi criteria cost function. The proposed algorithm is based on the use of the dynamic state-dependent policies which is implemented with a bio-inspired approach based on iterative trial/error paradigm. Our proposal is considered as a hybrid protocol: it combines on demand searching routes concept and proactive exploration concept. It uses also a multipoint relay mechanism for energy consumption in order to reduce the overhead generated by the exploration packets. Numerical results obtained with NS simulator for different static and mobility scenario show the efficiency of the adaptive approaches compared to traditional approaches and proves that such adaptive algorithms are very useful in tracking a phenomenon that evolves over time

This thesis addresses several aerospace guidance and decision making problems using both no cooperative and cooperative game theoretical solution concepts in the differential games framework. In the first part of the thesis, state dependent Riccati equation (SDRE) method has been extended to a zero-sum nonlinear differential games setting. This framework is used to study problems of intercepting a manoeuvring target, with and without terminal impact angle constraints, in the zero-sum differential games theory perspective. The guidance laws derived according to the proposed method are in closed from and online implementable. In the second part of the thesis, cooperative game theoretic concepts are applied to make a group of unmanned aerial vehicles (UAV) achieve rendezvous, in a given finite time horizon. An algorithm has been proposed that enables the UAVs to realize Nash bargaining solution. In this context, criteria for time consistency of a cooperative solution of nonzero-sum linear quadratic differential games have been studied. The problems where the UAVs try to achieve rendezvous by implementing cooperative game theoretic strategies, based on local information structure only, is also addressed.

Estudamos a Eletrodinâmica de Wheeler-Feynman usando um princípio variacional para um funcional de ação finito acoplado a um problema de valor na fronteira. Para trajetórias C2 por trechos, a condição de ponto crítico desse funcional fornece as equações de movimento de Wheeler-Feynman mais uma condição de continuidade dos momentos parciais e energias parciais, conhecida como condição de quina de Weierstrass-Erdmann. Estudamos em detalhe um sub-caso mais simples, onde os dados de fronteira têm um comprimento mínimo. Nesse caso, mostramos que a condição de extremo se reduz a um problema de valor na chegada para uma equação diferencial com retardo misto dependente do estado e do tipo neutro. Resolvemos numericamente esse problema usando um método de shooting e um método de Runge-Kutta de quarta ordem. Para os casos em que as fronteiras mínimas têm velocidades descontínuas, elaboramos uma técnica para resolver as condições de quina de Weierstrass-Erdmann junto com o problema de valor na chegada. As trajetórias com velocidades descontínuas previstas pelo método variacional foram verificadas por experimentos numéricos. Em um segundo desenvolvimento, para o caso mais difícil de fronteiras de comprimento arbitrário, implementamos um método de minimização com gradiente fraco para o princípio variacional e problema de fronteira acima citado. Elaboramos dois métodos numéricos, ambos implementados em MATLAB, para encontrar soluções do problema eletromagnético de dois corpos. O primeiro combina o método de elementos finitos com o método de Newton para encontrar as soluções que anulam o gradiente fraco do funcional para fronteiras genéricas. O segundo usa o método do declive máximo para encontrar as soluções que minimizam a ação. Nesses dois métodos as trajetórias são aproximadas dentro de um espaço de dimensão finita gerado por uma Galerkiana que suporta velocidades descontínuas. Foram realizados diversos testes e experimentos numéricos para verificar a convergência das trajetórias calculada numericamente; também comparamos os valores do funcional calculados numericamente com alguns resultados analíticos sobre órbitas circulares. / We study the Wheeler-Feynman electrodynamics using a variational principle for an action functional coupled to a finite boundary value problem. For piecewise C2 trajectories, the critical point condition for this functional gives the Wheeler-Feynman equations of motion in addition to a continuity condition of partial moments and partial energies, known as the Weierstrass-Erdmann corner conditions. In the simplest case, for the boundary value problem of shortest length, we show that the critical point condition reduces to a two-point boundary value problem for a state-dependent mixed-type neutral differential-delay equation. We solve this special problem numerically using a shooting method and a fourth order Runge-Kutta. For the cases where the boundary segment has discontinuous velocities we developed a technique to solve the Weierstrass-Erdmann corner conditions and the two-point boundary value problem together. The trajectories with discontinuous velocities presupposed by the variational method were verified by numerical experiments. In a second development, for the harder case with boundaries of arbitrary length, we implemented a method of minimization with weak gradient for the variational principle quoted above. Two numerical methods were implemented in MATLAB to find solutions of the two-body electromagnetic problem. The first combines the finite element method with Newtons method to find the solutions that vanish the weak gradient. The second uses the method of steepest descent to find the solutions that minimize the action. In both methods the trajectories are approximated within a finite-dimensional space generated by a Galerkian that supports discontinuous velocities. Many tests and numerical experiments were performed to verify the convergence of the numerically calculated trajectories; also were compared the values of the functional computed numerically with some known analytical results on circular orbits.

本論文主要是在agent-based計算經濟體系下，利用Holland(1975)所提的遺傳演算法(genetic algorithms)作為計算工具，分別探討連鎖店賽局及寡占市場廠商價格策略的生態演化。 在連鎖店賽局的研究中，藉由agent-based計算經濟分析掠奪性定價的特性，並進一步探討參賽者價格策略的共演化(co-evolutionary)特性，及多元均衡賽局中均衡移轉的動態過程。針對賽局中不同的不確定性進行模擬，結果顯示廠商長期總合行為是否穩定，和賽局中的不確定程度有相當的關聯。另外，弱獨占者和潛在競爭者的價格策略存在著共演化特性。在此演化賽局中，Nash均衡雖非穩定均衡解，但卻最常浮現在長期總合行為中。因此，Nsah均衡對agent-based演化賽局的結果而言，相當具有參考價值。在特定的不確定程度下，長期總合行為似乎只在某些特定的Nash均衡中徘徊。這些移轉途徑並不具有對稱性，甚至移轉速度也非對稱。本研究所呈現的演化結果跳脫一般對均衡的觀念，展現出傳統理論所無法預知的共演化特性，並呈現出非對稱的吸引環。 此外，同樣在Agent-based計算經濟下探討寡占市場廠商策略生態。本研究首先闡明N參賽者囚犯兩難重複賽局和N廠商寡占賽局之間的異同，經由寡占賽局廠商償付矩陣(payoff matrix)的狀態相依馬可夫移轉矩陣( state-dependent Markov transition matrix)性質，說明N廠商寡占賽局和N參賽者囚犯兩難重複賽局的差異。其次，透過三家廠商寡占賽局的模擬實驗，以遺傳演算法建構參賽廠商的適應性行為，分別以寡占市場生態上的表現型(phenotypes)和基因型(genotype)進行分析。20次模擬結果所呈現的最終市場狀態相當分歧，有形成吸引環的三廠商寡占市場、有收斂到價格戰的三廠商寡占市場。另外也成功的模擬出三廠商寡占市場演化至雙佔市場、甚或獨占市場的過程。但是，在眾多模擬中並沒有發現持續的勾結定價狀態，反而掠奪性價格是較主要的價格策略。這些結果相對於實際經濟社會中的寡占市場，給予一個活潑生動的範例。 / Recently, genetic algorithms have been extensively applied to modeling evolution game in agent-based computational economic.　While these applications advance our understanding of evolution game, they have generated some new phenomena that have not been well treated in conventional game theory. In the first topic, we shall systemize the study of one of these new phenomena, namely, coevolutionary instability. We exemplify the basic properties of coevolutionary instability by the chain store game, which is the game frequently used to study the role of reputation effects in economics.　In addition, we point out that, while, due to uncertainty effects, Nash equilibria can no longer be stable, and they can still help us predict the dynamic process of the game.　In particular, we can see that the dynamic process of the game is well captured by a few Nash equilibria and the transition among them.　A careful study can uncover several interesting patterns and we show the impact of uncertainty on these patterns. In the second topic, the relation between the N-person IPD game and the N-person oligopoly game is rigorously addressed.　Our analytical framework shows that due to the path-dependence of the payoff matrix of the oligopoly game, the two games in general are not close in spirit.　We then further explore the significance of the path-dependence property to the rich ecology of oligopoly from an evolutionary perspective.　More precisely, we simulated the evolution of a 3-person oligopoly game, and showed that the rich ecology of oligopoly can be exhibited by modeling the adaptive behavior of oligopolists with genetic algorithms.　The emergent behavior of oligopolists are presented and analyzed.　We indicate how the path-dependence nature may shed light on the phenotypes and genotypes coming into existence.

Estudamos a Eletrodinâmica de Wheeler-Feynman usando um princípio variacional para um funcional de ação finito acoplado a um problema de valor na fronteira. Para trajetórias C2 por trechos, a condição de ponto crítico desse funcional fornece as equações de movimento de Wheeler-Feynman mais uma condição de continuidade dos momentos parciais e energias parciais, conhecida como condição de quina de Weierstrass-Erdmann. Estudamos em detalhe um sub-caso mais simples, onde os dados de fronteira têm um comprimento mínimo. Nesse caso, mostramos que a condição de extremo se reduz a um problema de valor na chegada para uma equação diferencial com retardo misto dependente do estado e do tipo neutro. Resolvemos numericamente esse problema usando um método de shooting e um método de Runge-Kutta de quarta ordem. Para os casos em que as fronteiras mínimas têm velocidades descontínuas, elaboramos uma técnica para resolver as condições de quina de Weierstrass-Erdmann junto com o problema de valor na chegada. As trajetórias com velocidades descontínuas previstas pelo método variacional foram verificadas por experimentos numéricos. Em um segundo desenvolvimento, para o caso mais difícil de fronteiras de comprimento arbitrário, implementamos um método de minimização com gradiente fraco para o princípio variacional e problema de fronteira acima citado. Elaboramos dois métodos numéricos, ambos implementados em MATLAB, para encontrar soluções do problema eletromagnético de dois corpos. O primeiro combina o método de elementos finitos com o método de Newton para encontrar as soluções que anulam o gradiente fraco do funcional para fronteiras genéricas. O segundo usa o método do declive máximo para encontrar as soluções que minimizam a ação. Nesses dois métodos as trajetórias são aproximadas dentro de um espaço de dimensão finita gerado por uma Galerkiana que suporta velocidades descontínuas. Foram realizados diversos testes e experimentos numéricos para verificar a convergência das trajetórias calculada numericamente; também comparamos os valores do funcional calculados numericamente com alguns resultados analíticos sobre órbitas circulares. / We study the Wheeler-Feynman electrodynamics using a variational principle for an action functional coupled to a finite boundary value problem. For piecewise C2 trajectories, the critical point condition for this functional gives the Wheeler-Feynman equations of motion in addition to a continuity condition of partial moments and partial energies, known as the Weierstrass-Erdmann corner conditions. In the simplest case, for the boundary value problem of shortest length, we show that the critical point condition reduces to a two-point boundary value problem for a state-dependent mixed-type neutral differential-delay equation. We solve this special problem numerically using a shooting method and a fourth order Runge-Kutta. For the cases where the boundary segment has discontinuous velocities we developed a technique to solve the Weierstrass-Erdmann corner conditions and the two-point boundary value problem together. The trajectories with discontinuous velocities presupposed by the variational method were verified by numerical experiments. In a second development, for the harder case with boundaries of arbitrary length, we implemented a method of minimization with weak gradient for the variational principle quoted above. Two numerical methods were implemented in MATLAB to find solutions of the two-body electromagnetic problem. The first combines the finite element method with Newtons method to find the solutions that vanish the weak gradient. The second uses the method of steepest descent to find the solutions that minimize the action. In both methods the trajectories are approximated within a finite-dimensional space generated by a Galerkian that supports discontinuous velocities. Many tests and numerical experiments were performed to verify the convergence of the numerically calculated trajectories; also were compared the values of the functional computed numerically with some known analytical results on circular orbits.

Cette thèse est dédiée à l'analyse de stabilité des systèmes à pas d'échantillonnage variable et à la commande dynamique de l'échantillonnage. L'objectif est de concevoir des lois d'échantillonnage permettant de réduire la fréquence d'actualisation de la commande par retour d'état, tout en garantissant la stabilité du système.Tout d'abord, un aperçu des récents défis et axes de recherche sur les systèmes échantillonnés est présenté. Ensuite, une nouvelle approche de contrôle dynamique de l'échantillonnage, "échantillonnage dépendant de l'état", est proposée. Elle permet de concevoir hors-ligne un échantillonnage maximal dépendant de l'état défini sur des régions coniques de l'espace d'état, grâce à des LMIs.Plusieurs types de systèmes sont étudiés. Tout d'abord, le cas de système LTI idéal est considéré. La fonction d'échantillonnage est construite au moyen de polytopes convexes et de conditions de stabilité exponentielle de type Lyapunov-Razumikhin. Ensuite, la robustesse vis-à-vis des perturbations est incluse. Plusieurs applications sont proposées: analyse de stabilité robuste vis-à-vis des variations du pas d'échantillonnage, contrôles event-triggered et self-triggered, et échantillonnage dépendant de l'état. Enfin, le cas de système LTI perturbé à retard est traité. La construction de la fonction d'échantillonnage est basée sur des conditions de stabilité L2 et sur un nouveau type de fonctionnelles de Lyapunov-Krasovskii avec des matrices dépendant de l'état. Pour finir, le problème de stabilisation est traité, avec un nouveau contrôleur dont les gains commutent en fonction de l'état du système. Un co-design contrôleur/fonction d'échantillonnage est alors proposé / This PhD thesis is dedicated to the stability analysis of sampled-data systems with time-varying sampling, and to the dynamic control of the sampling instants. The main objective is to design sampling laws that allow for reducing the sampling frequency of state-feedback control for linear systems while ensuring the system's stability.First, an overview of the recent problems, challenges, and research directions regarding sampled-data systems is presented. Then, a novel dynamic sampling control approach, "state-dependent sampling", is proposed. It allows for designing offline a maximal state-dependent sampling map over conic regions of the state space, thanks to LMIs.Various classes of systems are considered throughout the thesis. First, we consider the case of ideal LTI systems, and propose a sampling map design based on the use of polytopic embeddings and Lyapunov-Razumikhin exponential stability conditions. Then, the robustness with respect to exogenous perturbations is included. Different applications are proposed: robust stability analysis with respect to time-varying sampling, as well as event-triggered, self-triggered, and state-dependent sampling control schemes. Finally, a sampling map design is proposed in the case of perturbed LTI systems with delay in the feedback control loop. It is based on L2-stability conditions and a novel type of Lyapunov-Krasovskii functionals with state-dependent matrices. Here, the stabilization issue is considered, and a new controller with gains that switch according to the system's state is presented. A co-design controller gains/sampling map is then proposed

We have examinined the problem of constructing efficient strategies for continuous-time dynamic asset allocation. In order to obtain efficient investment strategies; a stochastic optimal control approach was applied to find optimal transaction control. Two mathematical problems are formulized and studied: Model I; a dynamic programming approach that maximizes an isoelastic functional with respect to given underlying portfolio dynamics and Model II; a more sophisticated approach where a time-inconsistent state dependent mean-variance functional is considered. In contrast to the optimal controls for Model I, which are obtained by solving the Hamilton-Jacobi-Bellman (HJB) partial differential equation; the efficient strategies for Model II are constructed by attaining subgame perfect Nash equilibrium controls that satisfy the extended HJB equation, introduced by Björk et al. in [1]. Furthermore; comprehensive execution algorithms where designed with help from the generated results and several simulations are performed. The results reveal that optimality is obtained for Model I by holding a fix portfolio balance throughout the whole investment period and Model II suggests a continuous liquidation of the risky holdings as time evolves. A clear advantage of using Model II is concluded as it is far more efficient and actually takes time-inconsistency into consideration. / Vi har undersökt problemet som uppstår vid konstruktion av effektiva strategier för tidskontinuerlig dynamisk tillgångsallokering. Tillvägagångsättet för konstruktionen av strategierna har baserats på stokastisk optimal styrteori där optimal transaktionsstyrning beräknas. Två matematiska problem formulerades och betraktades: Modell I, en metod där dynamisk programmering används för att maximera en isoelastisk funktional med avseende på given underliggande portföljdynamik. Modell II, en mer sofistikerad metod som tar i beaktning en tidsinkonsistent och tillståndsberoende avvägning mellan förväntad avkastning och varians. Till skillnad från de optimala styrvariablerna för Modell I som satisfierar Hamilton-Jacobi-Bellmans (HJB) partiella differentialekvation, konstrueras de effektiva strategierna för Modell II genom att erhålla subgame perfekt Nashjämvikt. Dessa satisfierar den utökade HJB ekvationen som introduceras av Björk et al. i [1]. Vidare har övergripande exekveringsalgoritmer skapats med hjälp av resultaten och ett flertal simuleringar har producerats. Resultaten avslöjar att optimalitet för Modell I erhålls genom att hålla en fix portföljbalans mellan de riskfria och riskfyllda tillgångarna, genom hela investeringsperioden. Medan för Modell II föreslås en kontinuerlig likvidering av de riskfyllda tillgångarna i takt med, men inte proportionerligt mot, tidens gång. Slutsatsen är att det finns en tydlig fördel med användandet av Modell II eftersom att resultaten påvisar en påtagligt högre grad av effektivitet samt att modellen faktiskt tar hänsyn till tidsinkonsistens.