Relevant bibliographies by topics / Contrôle de trajectoire optimal

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  2. Dissertations / Theses
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  4. Book chapters
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Academic literature on the topic 'Contrôle de trajectoire optimal'

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Published: 16 November 2024

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Journal articles on the topic "Contrôle de trajectoire optimal"

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Daneault, Serge. "La poursuite d’une bonne mort est-elle une utopie ?" Articles 20, no. 1 (May 8, 2008): 27–33. http://dx.doi.org/10.7202/017944ar.

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Résumé La préoccupation de la bonne mort se situe dans la mouvance intellectuelle de ce nouveau millénaire caractérisé par une désillusion généralisée à l’égard de la science et de la technologie et un vacuum spirituel. La réalité de la mort n’est pas forcément le reflet de ce qui se passe dans les milieux de soins palliatifs. La majorité des décès surviennent dans les unités de soins actifs des hôpitaux de courte durée ou dans les centres hospitaliers de soins prolongés, endroits où il est possible que le soulagement de la souffrance ne soit pas optimal. Les caractéristiques de la bonne mort sont surtout axées sur le contrôle et l’autonomie, valeurs éminemment individuelles. L’utilisation de ces critères pour évaluer les trajectoires de soins de fin de vie fait moins l’unanimité que la nécessité d’assurer à tous l’accès à des soins palliatifs de qualité.
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Podobryaev, A. V. "Symmetric Extremal Trajectories in Left-Invariant Optimal Control Problems." Nelineinaya Dinamika 15, no. 4 (2019): 569–75. http://dx.doi.org/10.20537/nd190416.

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SAIDI, IMEN, and NAHLA TOUATI. "APPRENTISSAGE DE COMMANDE POUR LE SUIVI DE TRAJECTOIRE D'UN PENDULE INVERSÉ À ROUE D'INERTIE NON LINÉAIRE." REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE 68, no. 4 (December 23, 2023): 424–30. http://dx.doi.org/10.59277/rrst-ee.2023.4.17.

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Cet article propose le contrôle d'apprentissage itératif pour les systèmes sous-actionnés non linéaires. Pour améliorer la vitesse de convergence du contrôle d'apprentissage itératif pour de tels systèmes et réduire la fluctuation de l'erreur du système, un algorithme de contrôle d'apprentissage itératif en boucle fermée de type D à gain variable exponentiel a été choisi. L'analyse de simulation MATLAB a ensuite été réalisée sur un système sous-actionné, non linéaire et instable, à savoir le pendule inversé à roue d'inertie. Les résultats de la simulation montrent que l'algorithme est efficace. De bonnes performances de suivi ont été obtenues. Le système converge vers des cycles limites stables après quelques itérations, garantissant des erreurs fluides et une vitesse de convergence satisfaisante.
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Foehn, Philipp, Angel Romero, and Davide Scaramuzza. "Time-optimal planning for quadrotor waypoint flight." Science Robotics 6, no. 56 (July 21, 2021): eabh1221. http://dx.doi.org/10.1126/scirobotics.abh1221.

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Quadrotors are among the most agile flying robots. However, planning time-optimal trajectories at the actuation limit through multiple waypoints remains an open problem. This is crucial for applications such as inspection, delivery, search and rescue, and drone racing. Early works used polynomial trajectory formulations, which do not exploit the full actuator potential because of their inherent smoothness. Recent works resorted to numerical optimization but require waypoints to be allocated as costs or constraints at specific discrete times. However, this time allocation is a priori unknown and renders previous works incapable of producing truly time-optimal trajectories. To generate truly time-optimal trajectories, we propose a solution to the time allocation problem while exploiting the full quadrotor’s actuator potential. We achieve this by introducing a formulation of progress along the trajectory, which enables the simultaneous optimization of the time allocation and the trajectory itself. We compare our method against related approaches and validate it in real-world flights in one of the world’s largest motion-capture systems, where we outperform human expert drone pilots in a drone-racing task.
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Simon, Dan, and Can Isik. "Optimal trigonometric robot joint trajectories." Robotica 9, no. 4 (December 1991): 379–86. http://dx.doi.org/10.1017/s0263574700000552.

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SUMMARYInterpolation of a robot joint trajectory is realized using trigonometric splines. This original application has several advantages over existing methods (e.g. those using algebraic splines). For example, the computational expense is lower, more constraints can be imposed on the trajectory, obstacle avoidance can be implemented in real time, and smoother trajectories are obtained. Some of the spline parameters can be chosen to minimize an objective function (e.g. minimum jerk or minimum energy). If jerk is minimized, the optimization has a closed form solution. This paper introduces a trajectory interpolation algorithm, discusses a method for path optimization, and includes examples.
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Liu, Ke, Guanzheng Wen, Yao Fu, and Honglin Wang. "A Hierarchical Lane-Changing Trajectory Planning Method Based on the Least Action Principle." Actuators 13, no. 1 (December 26, 2023): 10. http://dx.doi.org/10.3390/act13010010.

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This paper presents a hierarchical lane-changing trajectory planner based on the least action principle for autonomous driving. Our approach aims to achieve reliable real-time avoidance of static and moving obstacles in multi-vehicle interaction scenarios on structured urban roads. Unlike previous studies that rely on subjective weight allocation and single weighting methods, we propose a novel trajectory planning strategy that decomposes the process into two stages: candidate trajectory generation and optimal trajectory decision-making. The candidate trajectory generation employs a path-velocity decomposition method, using B-spline curves to generate a multi-objective optimal lane-changing candidate path. Collision checking eliminates paths at risk of collision with static obstacles. Dynamic programming (DP) and quadratic programming (QP) are then used to plan the velocity of safe paths, generating candidate lane-changing trajectories based on curvature checking. The optimal trajectory decision-making process follows the decision mechanism of excellent drivers. We introduce a comprehensive evaluation function, the average action, which considers safety, comfort, and efficiency based on the least action principle. Feasible trajectories are ranked based on their average action, and the trajectory with the minimum average action and no collision risk with moving obstacles is selected as the tracking target. The effectiveness of the proposed method is validated through two common lane-changing scenarios. The results demonstrate that our approach enables smooth, efficient, and safe lane-changing while effectively tracking the planned velocity and path. This method offers a solution to local trajectory planning problems in complex environments and holds promising prospects in the field of autonomous driving.
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Yin, Haolin, Baoquan Li, Hai Zhu, and Lintao Shi. "Kinodynamic RRT* Based UAV Optimal State Motion Planning with Collision Risk Awareness." Information Technology and Control 52, no. 3 (September 26, 2023): 665–79. http://dx.doi.org/10.5755/j01.itc.52.3.33583.

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In this paper, an autonomous navigation strategy is proposed for unmanned aerial vehicles (UAVs) based on consideration of dynamic sampling and field of view (FOV). Compare to search-based motion planning, sampling-based kinodynamic planning schemes can often find feasible trajectories in complex environments. Specifically, a global trajectory is first generated with physical information, and an expansion algorithm is constructed regarding to kinodynamic rapidly-exploring random tree* (KRRT*). Then, a KRRT* expansion strategy is designed to find local collision-free trajectories. In trajectory optimization, bending radius, collision risk function, and yaw angle penalty term are defined by taking into account onboard sensor FOV and potentialrisk. Then, smooth and dynamic feasible terms are penalized based on initial trajectory generation. Trajectories are refined by time reallocation, and weights are solved by optimization. Effectiveness of the proposed strategy is demonstrated by both simulation and experiment.
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Al Younes, Younes, and Martin Barczyk. "Nonlinear Model Predictive Horizon for Optimal Trajectory Generation." Robotics 10, no. 3 (July 14, 2021): 90. http://dx.doi.org/10.3390/robotics10030090.

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This paper presents a trajectory generation method for a nonlinear system under closed-loop control (here a quadrotor drone) motivated by the Nonlinear Model Predictive Control (NMPC) method. Unlike NMPC, the proposed method employs a closed-loop system dynamics model within the optimization problem to efficiently generate reference trajectories in real time. We call this approach the Nonlinear Model Predictive Horizon (NMPH). The closed-loop model used within NMPH employs a feedback linearization control law design to decrease the nonconvexity of the optimization problem and thus achieve faster convergence. For robust trajectory planning in a dynamically changing environment, static and dynamic obstacle constraints are supported within the NMPH algorithm. Our algorithm is applied to a quadrotor system to generate optimal reference trajectories in 3D, and several simulation scenarios are provided to validate the features and evaluate the performance of the proposed methodology.
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Peralta-Caprachin, Henry, Raul Angeles-Orahulio, and Ernesto Paiva-Peredo. "Design and Position Control of a Robot with 5 Degrees of Freedom." International Journal of Mechanical Engineering and Robotics Research 13, no. 2 (2024): 241–48. http://dx.doi.org/10.18178/ijmerr.13.2.241-248.

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In recent decades, robotics and artificial intelligence have gained significant importance for their involvement in various industrial processes currently at their peak. Nevertheless, advanced robots are not designed explicitly for lemon supply. This research aims to develop a manipulator robot with 5 degrees of freedom and control its trajectories for lemon supply purposes. To achieve this goal, kinematic and dynamic calculations of the manipulator robot were performed, along with the development of programming code in Matlab to determine its trajectories, positions, speeds, and accelerations. In addition, the Proportional Integral Derivative (PID) tuner was used to obtain the optimal controller parameters and ensure accurate joint trajectory generation.
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Zhao, Jiangying, Yongbiao Hu, Chengshuo Liu, Mingrui Tian, and Xiaohua Xia. "Spline-Based Optimal Trajectory Generation for Autonomous Excavator." Machines 10, no. 7 (July 3, 2022): 538. http://dx.doi.org/10.3390/machines10070538.

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In this paper, we propose a novel trajectory generation method for autonomous excavator teach-and-plan applications. Rather than controlling the excavator to precisely follow the teaching path, the proposed method transforms the arbitrary slow and jerky trajectory of human excavation into a topologically equivalent path that is guaranteed to be fast, smooth and dynamically feasible. This method optimizes trajectories in both time and jerk aspects. A spline is used to connect these waypoints, which are topologically equivalent to the human teaching path. Then the trajectory is reparametrized to obtain the minimum time-jerk trajectory with the kinodynamic constraints. The optimal time-jerk trajectory generation method is both formulated using nonlinear programming and conducted iteratively. The framework proposed in this paper was integrated into a complete autonomous excavation platform and was validated to achieve aggressive excavation in a field environment.
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Dissertations / Theses on the topic "Contrôle de trajectoire optimal"

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Maillot, Thibault. "Planification de trajectoire pour drones de combat." Phd thesis, Toulon, 2013. http://tel.archives-ouvertes.fr/tel-00954584.

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L'objectif principal de ce travail est l'étude de la planification de trajectoires pour des drones de type HALE ou MALE. Les modèles cinématiques de ces drones sont étudiés. Les drones HALE sont modélisés par le système de Dubins. Pour les drones MALE, le modèle est construit en étudiant le repère cinématique du drone. Nous considérons les problèmes de planification de trajectoires point-point et point-pattern. Il s'agit, à partir de la position courante du drone, de rejoindre un point ou une figure prédéfinie dans l'espace. La planification point-point est abordée sous forme d'un problème de contrôle optimal. Deux méthodes sont proposées pour résoudre le problème point-pattern. D'abord nous présentons la synthèse en temps minimal pour le système de Dubins. Ensuite, nous développons une méthode basée sur le principe de LaSalle. La première méthode est utilisée au sein d'un algorithme de planification pour des drones HALE. La deuxième permet de stabiliser les deux types de drones considérés vers un pattern. Nous proposons une extension des algorithmes de planification développés, basée sur une discrétisation del'espace grâce aux graphes de Voronoï et une méthode de planification discrète, pour construire des trajectoiresdans des milieux encombrés. Nous étudions également le problème de couplage drone/capteur. Il s'agit de calculer une trajectoire permettant de satisfaire les objectifs du drone et de son capteur (une caméra). L'algorithme proposé est construit à partir de la résolution d'un problème quadratique sous contraintes.Dans une seconde partie, nous analysons un problème de contrôle optimal inverse. Celui-ci permet d'améliorer les résultats des méthodes de planification en s'inspirant du comportement des pilotes. Après avoir posé le problème, les résultats théoriques sont exposés et le cas particulier du système de Dubins est étudié en pratique.
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Ajami, Alain. "Modélisation et simulation d'une station mono-opérateur pour le contrôle de drones et la planification de trajectoire." Thesis, Toulon, 2013. http://www.theses.fr/2013TOUL0009/document.

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Ce travail s’inscrit dans le projet plus global SHARE dont l’objectif principal est de concevoir une station de contrôle sol universelle mono-opérateur de nouvelle génération pour le contrôle et la commande de drones à voilure fixe et voilure tournante.L’objectif de cette thèse est de développer un simulateur générique de la station de contrôle capable de simuler en temps réels les différents types de drones, les capteurs embarqués (caméra), l’environnement et les différentes missions militaires définies par le standard STANAG 4586. Après une modélisation des différentes parties de la station, nous présentons l’architecture adoptée pour le simulateur et le module de contrôle. Ce dernier est divisé en plusieurs niveaux hiérarchiques, dont le niveau supérieur contient les algorithmes de planification de trajectoire pour les drones à voilure fixe HALE (haute altitude, longue endurance). Ces algorithmes servent à calculer un chemin admissible entre un point de départ et un point d’arrivée en minimisant une fonction de coût.Enfin nous avons développé un système d’aide à la décision pour la gestion en ligne des missions, capable de réaliser une sélection d’objectifs, et une sélection du meilleur chemin proposé par les algorithmes de planification de trajectoire. Cet outil a pour objectif d’aider l’opérateur de la station à prendre la meilleure décision en maximisant les récompenses obtenues lors de la réalisation des objectifs et en minimisant certains critères tels que la consommation des ressources, le danger, les conditions météorologiques, etc
The presented work is part of a larger project called SHARE, which consists in developing a universal new generation ground control station for the monitoring and the control of fixed and rotary wing UAVs (Unmanned Aerial Vehicle).The objective of this PhD thesis is to develop a generic ground control station simulator capable of simulating in real time different types of UAVs, onboard sensors, several flight environments, and various military missions which are defined according to the STANAG 4586 standard. First, we introduce the model of the different parts of the station, and then we present the architecture adopted for the simulator and the control module. The latter is divided into several hierarchical levels; the upper level contains the path planning algorithms for fixed wing HALE (High Altitude, Long Endurance) UAV. These algorithms are used to calculate an admissible path between initial and final position by minimizing a cost function.Finally, in order to manage missions online, we developed a decision support system that is capable of performing a variety of objectives. This system also supplies the operator the best paths proposed by planning algorithms. This tool aims to help the station operator to make the decision by maximizing the rewards obtained during the achieving the objectives and minimizing certain criteria (resource consumption, danger, weather,..)
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Ašković, Veljko. "Aerial vehicle guidance problem through the Pontryagin Maximum Principle and Hamilton Jacobi Bellman approach." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS553.

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La thèse comporte deux volets principaux: Le premier volet, d'ordre théorique, porte sur le développement asymptotique de la fonction valeur associée à un problème de contrôle optimal lorsque l'horizon tend vers l'infini. Un développement asymptotique à deux termes a été démontré d'abord dans le cas linéaire quadratique puis ensuite a été étendu au cas non linéaire dans la classe de systèmes dissipatifs. La seconde partie de la thèse porte sur la résolution numérique d'un problème de guidage de véhicules aériens. Après avoir modélisé le problème, nous mettons en œuvre trois méthodes afin de résoudre des variantes du problème: une méthode directe, une méthode indirecte basée sur la continuation et le tir et enfin l'approche Hamilton Jacobi Bellman. Cette dernière nous permet également d'évaluer numériquement des domaines atteignables par notre système
This thesis is mainly composed of two parts. In the first part, we investigate the large time behavior of the value function associated to an optimal control problem in the finite dimensional case. We first establish the large time asymptotic expansion in the linear quadratic (LQ) theory. We then generalize this expansion to nonlinear dynamical systems more precisely within the class of dissipative systems. In the second part, we solve numerically the guidance problem of an aerial vehicle. We first model mathematically the equations of motion. Then, we implement three methods in order to solve the problem: a direct method, an indirect method based on the continuation process and the shooting method. Finally, we implement a numerical method derived from the Hamilton Jacobi Bellman theory in order to compute optimal trajectories and at the same time the reachable sets
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Rousseau, Gauthier. "Optimal trajectory planning and predictive control for cinematographic flight plans with quadrotors." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLC086/document.

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Cette thèse s'intéresse à la réalisation autonome de plans de vol cinématographiques par un quadrotor équipé d'une caméra. Ces plans de vol consistent en une série de points de passage à rejoindre successivement, en adoptant diverses méthodes de prise de vue et en respectant des références de vitesses ainsi que des couloirs de vols. Une étude approfondie de la dynamique du quadrotor est tout d'abord proposée et utilisée pour construire un modèle linéarisé du drone autour de l'équilibre de vol stationnaire. L'analyse de ce modèle linéaire permet de mettre en évidence l'impact de l'inertie des rotors du drone dans sa dynamique, notamment l'apparition d'un comportement à non minimum de phase en roulis ou tangage, lorsque les moteurs sont inclinés. Dans un second temps, deux algorithmes de génération de trajectoires lisses, faisables et adaptées à la cinématographie sont proposés. La faisabilité de la trajectoire est garantie par le respect de contraintes sur ses dérivées temporelle, adaptées pour la cinématographie et obtenue grâce à l'étude du modèle non linéaire du drone. Le premier repose sur une optimisation bi-niveaux d'une trajectoire polynomiale par morceaux, dans le but de trouver la plus rapide des trajectoires à minimum de jerk permettant d'accomplir la mission. Le second algorithme consiste en la génération de trajectoires B-spline non-uniformes à durée minimale. Pour les deux solutions, une étude de l’initialisation du problème d'optimisation est présentée, de même qu'une analyse de leurs avantages et limitations. Pour ce faire, elles sont notamment confrontées à des simulations et vols extérieurs. Enfin, une loi de commande prédictive est proposée pour asservir les mouvements de la caméra embarquée de manière douce et précise
This thesis focuses on the autonomous performance of cinematographic flight plans by camera equipped quadrotors. These flight plans consist in a series of waypoints to join while adopting various camera behaviors, along with speed references and flight corridors. First, an in depth study of the nonlinear dynamics of the drone is proposed, which is then used to derive a linear model of the system around the hovering equilibrium. An analysis of this linear model allows us to emphasize the impact of the inertia of the propellers when the latter are tilted, such as the apparition of a nonminimum phase behavior of the pitch or roll dynamics. Then, two algorithms are proposed to generate smooth and feasible cinematographic trajectories. The feasibility of the trajectory is ensured by constraints on its time derivatives, suited for cinematography and obtained with the use of the nonlinear model of the drone. The first algorithm proposed in this work is based on a bi-level optimization of a piecewise polynomial trajectory, in order to find the fastest feasible minimum jerk trajectory to perform the flight plan. The second algorithm consists in the generation of feasible, minimum time, non-uniform B-spline trajectories. For both solutions, a study of the initilization of the optimization problem is proposed, as well as a discussion about their advantages and limitations. To this aim, they are notably confronted to simulations and outdoor flight experiments. Finally, a predictive control law is proposed to smoothly and accurately control the onboard camera
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Leparoux, Clara. "Optimal control under uncertainties for the vertical landing of the first stage of a reusable launch vehicle." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAE007.

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Les travaux de cette thèse portent sur le développement d'une méthode robuste de planification de trajectoire et de contrôle optimal. Ils apportent des justifications théoriques à la méthode présentée, prouvant l'existence de solutions au problème formulé. Enfin, la méthode est appliquée à un problème de planification de trajectoire pour l'atterrissage vertical d'un premier étage de lanceur réutilisable. Les contributions proposées sont les suivantes
The work in this thesis focuses on the development of a robust trajectory planning and optimal control method. It provides theoretical justifications for the method presented, proving the existence of solutions to the problem formulated. Finally, the method is applied to a trajectory planning problem for the vertical landing of a reusable launch vehicle first stage
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Pham, Quang-Cuong. "Etude de trajectoires locomotrices humaines." Paris 6, 2009. http://www.theses.fr/2009PA066535.

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La locomotion humaine est une activité motrice, sensorielle et cognitive qui fait intervenir de multiples niveaux de contrôle, comme la production de patterns rythmiques des membres inférieurs, l'ajustement postural du haut du corps pour la stabilisation ou encore la formation de trajectoires du corps entier dans l'espace. L'objectif principal de cette thèse est de fournir quelques éléments decompréhension du dernier aspect. En analysant les résultats d'une série d'expériences, nous montrons que les trajectoires locomotrices sont stéréotypées, c'est-à-dire qu'elles sont semblables à travers différents essais d'un même sujet, à travers différents sujets, mais aussi à travers différentes conditions sensorielles (marcher avec ou sans vision) et motrices (marcher en avant ou en arrière, à vitesse normale ou rapide). Ces observations suggèrent que les trajectoires locomotrices sont planifiées et contrôlées à un haut niveau cognitif et, dans une certaine mesure, indépendamment de leur implémentation sensori-motrice. En analysant plus en détail la variabilité de ces trajectories, nous soutenons qu'une combinaison de processus en boucle ouverte et en boucle fermée préside à la formation de trajectoires locomotrices et nous discutons de la nature précise du contrôle en boucle fermée en question. Enfin, nous développons des modèles déterministes et stochastiques qui permettent de confirmer les résultats expérimentaux, en même temps qu'ils organisent ceux-ci dans le cadre théorique du contrôle optimal.
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Homsi, Saed Al. "Online generation of time- optimal trajectories for industrial robots in dynamic environments." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAT027/document.

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Nous observons ces dernières années un besoin grandissant dans l’industrie pour des robots capables d’interagir et de coopérer dans des environnements confinés. Cependant, aujourd’hui encore, la définition de trajectoires sûres pour les robots industriels doit être faite manuellement par l’utilisateur et le logiciel ne dispose que de peu d’autonomie pour réagir aux modifications de l’environnement. Cette thèse vise à produire une structure logicielle innovante pour gérer l’évitement d’obstacles en temps réel pour des robots manipulateurs évoluant dans des environnements dynamiques. Nous avons développé pour cela un algorithme temps réel de génération de trajectoires qui supprime de façon automatique l’étape fastidieuse de définition d’une trajectoire sûre pour le robot.La valeur ajoutée de cette thèse réside dans le fait que nous intégrons le problème de contrôle optimal dans le concept de hiérarchie de tâches pour résoudre un problème d’optimisation non-linéaire efficacement et en temps réel sur un système embarqué aux ressources limitées. Notre approche utilise une commande prédictive (MPC) qui non seulement améliore la réactivité de notre système mais présente aussi l’avantage de pouvoir produire une bonne approximation linéaire des contraintes d’évitement de collision. La stratégie de contrôle présentée dans cette thèse a été validée à l’aide de plusieurs expérimentations en simulations et sur systèmes réels. Les résultats démontrent l’efficacité, la réactivité et la robustesse de cette nouvelle structure de contrôle lorsqu’elle est utilisée dans des environnements dynamiques
In the field of industrial robots, there is a growing need for having cooperative robots that interact with each other and share work spaces. Currently, industrial robotic systems still rely on hard coded motions with limited ability to react autonomously to dynamic changes in the environment. This thesis focuses on providing a novel framework to deal with real-time collision avoidance for robots performing tasks in a dynamic environment. We develop a reactive trajectory generation algorithm that reacts in real time, removes the fastidious optimization process which is traditionally executed by hand by handling it automatically, and provides a practical way of generating locally time optimal solutions.The novelty in this thesis is in the way we integrate the proposed time optimality problem in a task priority framework to solve a nonlinear optimization problem efficiently in real time using an embedded system with limited resources. Our approach is applied in a Model Predictive Control (MPC) setting, which not only improves reactivity of the system but presents a possibility to obtain accurate local linear approximations of the collision avoidance constraint. The control strategies presented in this thesis have been validated through various simulations and real-world robot experiments. The results demonstrate the effectiveness of the new control structure and its reactivity and robustness when working in dynamic environments
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Nour, Chadi. "L'équation de Hamlilton-Jacobi en contrôle optimal : dualité et géodésiques." Phd thesis, Université Claude Bernard - Lyon I, 2003. http://tel.archives-ouvertes.fr/tel-00003973.

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L'objet principal de cette thèse est l'application de méthodes nouvelles inspirées de l'analyse non-lisse et impliquant l'équation Hamilton-Jacobi pour l'étude de certains problèmes en théorie du contrôle. Notre travail se compose de trois parties : * La première partie est consacrée à la généralisation d'un résultat célèbre de R. Vinter (1993) qui porte sur la dualité non-convexe en contrôle optimal. Entre autre, ceci mène à une nouvelle caractérisation de la fonction temps minimal. * Dans la deuxième partie, nous étudions l'équation classique d'Hamilton-Jacobi de la fonction temps minimal mais dans un domaine contenant l'origine. Nous démontrons l'existence de solutions et même d'une solution minimale de cette équation, et établissons des liens avec les trajectoires géodésiques. * La dernière partie de cette thèese est consacr\ée à l'étude des boucles minimales pour les systèmes de contrôle. Nous donnons des conditions nécessaires et suffisantes pour l'existence de ces boucles en un point donné.
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Dufour, Kévin. "Génération automatique et sécuritaire de trajectoires pour un robot collaboratif." Mémoire, Université de Sherbrooke, 2017. http://hdl.handle.net/11143/11810.

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Parce que la robotique collaborative vise à libérer les robots des barrières physiques les séparant des opérateurs humains, de nouveaux défis apparaissent autour de la sécurité de ces derniers. S'il est possible de diminuer la dangerosité des robots en amont de leur conception, les logiciels qui les contrôlent doivent impérativement intégrer des mesures de sécurité, afin d'être compatibles avec des environnements humains dynamiques. Les algorithmes classiques de planification de trajectoire nécessitant de lourds calculs, il est avantageux de modifier la trajectoire en temps réel pour l'adapter à l'environnement dangereux. Dans ce projet de recherche, un algorithme de cinématique inverse, sous forme de problème d'optimisation, est utilisé afin de générer la commande du robot à partir d'une trajectoire définie hors-ligne. L'ajout de contraintes de sécurité à ce problème est particulièrement étudié : dans un premier temps, l'indice de manipulabilité, qui traduit la distance du robot à une configuration singulière, est considéré. Ainsi, il doit être maximisé tout au long de la trajectoire afin d'assurer la meilleure mobilité disponible. Dans un deuxième temps, le facteur humain a été intégré par la prise en compte du confort de celui-ci : afin de réduire le stress éprouvé par l'opérateur face à un robot aux mouvements imprévisibles, on s'assure de minimiser la distance entre l'effecteur et le regard de l'humain pour garantir une plus grande visibilité de la tâche. Dans les deux cas, nous avons présenté une formulation originale de ces critères afin de les intégrer dans le problème d'optimisation. Par ailleurs la contrainte d'évitement d'obstacles a aussi été utilisée, de même que la relaxation de la trajectoire, qui permet au robot de dévier un peu de cette dernière pendant une portion de la durée de la tâche. Enfin des tests en simulation et avec le robot réel Baxter de Rethink Robotics ont permis de valider notre approche et de vérifier les performances en conditions réelles, en utilisant une caméra RGB-D et un logiciel de détection d'humain en temps réel.
Abstract : Because collaborative robots are aimed at working in the vicinity of human workers without physical security fences, they bring new challenges about security. Even if robots can be conceived to be less harmful, their software has to integrate security features in order to be suitable for dynamic human environments. Since classical path planning algorithms require heavy calculations, it is interesting to modify the trajectory in real time to adapt it to the dangerous environment. In this research project, an inverse kinematics solver, in the form of an optimization problem, is used to generate the command of the robot to follow a trajectory defined offline. The addition of security constraints is studied: first, the manipulability index, which reflects the distance of the robot to singular configurations, is considered. Thus, it should be maximized all along the trajectory to ensure the best mobility available. Then the human is integrated by taking into account its comfort: in order to reduce the stress of working near an unpredictable moving robot, the distance between the end-effector and the human gaze is minimized to guarantee a greater visibility of the task. In both cases, we have presented a new formulation of those criteria to integrate them into the optimization problem. Moreover, the collision avoidance constraint is used, as well as the trajectory relaxation, which allows the robot to deviate from its trajectory for a certain amount of time during the task. Finally tests in simulation and with the real Baxter robot from Rethink Robotics validated our approach and the performance has been evaluated in real conditions, using a RGB-D camera and a real time human tracker software.
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10

Talgorn, Bastien. "Décollage en cas de panne moteur : conception automatisée de trajectoire optimale." Toulouse 3, 2011. http://thesesups.ups-tlse.fr/5019/.

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En cas de panne moteur durant le décollage d'un avion, il existe une vitesse jusqu'à laquelle l'avion peut freiner. Au-delà de cette vitesse, l'avion est obligé de poursuivre le décollage le long de la trajectoire SID (Standard Instrument Departure) malgré la perte de poussée induite par la panne. Les paramètres de décollage doivent être choisis de façon à assurer la sécurité de l'avion dans chacune de ces deux situations. En terrain montagneux, les contraintes d'obstacles peuvent sévèrement pénaliser la masse maximale admissible au décollage de l'avion (MMD). Il est alors possible d'utiliser une trajectoire alternative, l'EOSID (Engine Out SID) dont la trace au sol est différente de la SID. Elle n'est utilisée qu'en cas de panne moteur et survole un relief moins pénalisant. Cela permet de réduire les contraintes réglementaires de passage des obstacles en cas de panne moteur et d'augmenter la masse de l'avion au décollage. La conception d'une EOSID est un processus itératif, réalisé manuellement au sol et nécessitant l'usage de plusieurs outils informatiques différents. L'objectif de cette thèse est de formaliser et d'automatiser ce processus afin d'améliorer la qualité de la trajectoire obtenue et de réduire la charge de travail nécessaire à sa conception. Pour ce faire, le processus de conception a été analysé puis modélisé sous la forme d'un problème d'optimisation dont l'objectif est de maximiser la MMD, tout en conservant une trajectoire suffisamment simple. Une méthode d'estimation de la complexité de la trajectoire a donc été définie puis intégrée avec la masse au sein d'un critère unique. Le problème est ensuite résolu à l'aide d'un algorithme génétique ad hoc
In case of engine failure during aircraft takeoff, there is a speed until which the aircraft can still break to abort the takeoff (Rejected takeoff procedure). Above this speed, the aircraft shall continue the takeoff along the SID trajectory (Standard Instrument Departure) despite the lack of thrust caused by the engine failure. The takeoff parameters must be chosen so that the security of the aircraft is guaranteed in both situations. In mountainous landscape, the obstacle clearance constraints can severely penalise the maximum takeoff weight of the aircraft. In this situation, it is possible to use an alternate trajectory: the EOSID (Engine Out Standard Instrument Departure). The ground track of the EOSID is different from the SID. This trajectory, which is only used in case of engine failure, flies over a relief that is less penalizing. This allows to reduce the regulatory obstacle clearance constraints in engine failure case and to increase the aircraft takeoff weight. The conception of an EOSID is an iterative manual on-ground process that needs several softwares. The aim of this thesis is to formulate and automate this process so as to improve the trajectory quality and to reduce the conception workload. In this aim, the conception process has been analysed and modelled as an optimization problem the objective of which is to maximise the maximum takeoff weight and to minimize the trajectory complexity. A trajectory complexity estimation method has hence been defined and integrated along with the weight within a single criterion. Then the problem is solved with a genetic algorithm that has been developed specifically to handle the trajectory definition format
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Books on the topic "Contrôle de trajectoire optimal"

1

E, Kim, and Ames Research Center, eds. Optimal helicopter trajectory planning for terrain following flight. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1990.

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Bless, Robert R. Variational trajectory optimization tool set: Technical description and user's manual. Hampton, Va: Langley Research Center, 1993.

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E, Kim, and Ames Research Center, eds. Optimal helicopter trajectory planning for terrain following flight: Final report. Atlanta, Ga: School of Aerospace Engineering, Georgia Institute of Technology, 1990.

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J, Calise Anthony, Moerder Daniel D, and United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., eds. Piloted simulation of an algorithm for onboard control of time-optimal intercept. [Washington, DC]: National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1985.

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S, Naidu D. Fuel-optimal trajectories of aeroassisted orbital transfer with plane change. Norfolk, Va: Old Dominion University Research Foundation, Dept. of Electrical and Computer Engineering, College of Engineering and Technology, Old Dominion University, 1989.

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S, Naidu D. Fuel-optimal trajectories of aeroassisted orbital transfer with plane change. Norfolk, Va: Old Dominion University Research Foundation, Dept. of Electrical and Computer Engineering, College of Engineering and Technology, Old Dominion University, 1989.

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Bless, Robert R. Time-domain finite elements in optimal control with application to launch-vehicle guidance. Hampton, Va: Langley Research Center, 1991.

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United States. National Aeronautics and Space Administration., ed. Hybrid motion planning with multiple destinations: Annual technical report : reporting period 06/10/97 through 06/10/98. [Washington, DC: National Aeronautics and Space Administration, 1998.

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Markopoulos, Nikos. Analytical investigations in aircraft and spacecraft trajectory optimization and optimal guidance / by Nikos Markopoulos and Anthony J. Calise. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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Georgia Institute of Technology. School of Aerospace Engineering. and Dryden Flight Research Facility, eds. A comparison of time-optimal interception trajectories for the F-8 and F-15: Final report. Atlanta, GA: Georgia Institute of Technology, School of Aerospace Engineering, 1990.

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Book chapters on the topic "Contrôle de trajectoire optimal"

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Aschepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Small Increments of a Trajectory." In Optimal Control, 115–23. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49781-5_10.

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Ashchepkov, Leonid T., Dmitriy V. Dolgy, Taekyun Kim, and Ravi P. Agarwal. "Small Increments of a Trajectory." In Optimal Control, 117–26. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91029-7_10.

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Löber, Jakob. "Optimal Control." In Optimal Trajectory Tracking of Nonlinear Dynamical Systems, 79–118. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46574-6_3.

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Betts, John T. "Trajectory Optimization Using Sparse Sequential Quadratic Programming." In Optimal Control, 115–28. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_9.

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Sonnevend, G. "Constructing Feedback Control in Differential Games by Use of “Central” Trajectories." In Optimal Control, 221–47. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_17.

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Sachs, Gottfried, Klaus Lesch, Hans Georg Bock, and Marc Steinbach. "Periodic Optimal Trajectories with Singular Control for Aircraft with High Aerodynamic Efficiency." In Optimal Control, 289–304. Basel: Birkhäuser Basel, 1993. http://dx.doi.org/10.1007/978-3-0348-7539-4_21.

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Järmark, Bernt, and Henrick Bengtsson. "Near-Optimal Flight Trajectories Generated by Neural Networks." In Computational Optimal Control, 319–28. Basel: Birkhäuser Basel, 1994. http://dx.doi.org/10.1007/978-3-0348-8497-6_25.

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Bonnard, Bernard, and Monique Chyba. "Singular Trajectories in Optimal Control." In Encyclopedia of Systems and Control, 1274–79. London: Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-5058-9_49.

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Bonnard, Bernard, and Monique Chyba. "Singular Trajectories in Optimal Control." In Encyclopedia of Systems and Control, 1–8. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5102-9_49-1.

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Bonnard, Bernard, and Monique Chyba. "Singular Trajectories in Optimal Control." In Encyclopedia of Systems and Control, 2069–74. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-44184-5_49.

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Conference papers on the topic "Contrôle de trajectoire optimal"

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Galisteu, Danilo, Florian Adolf, Jörg Dittrich, Falk Sachs, and Holger Duda. "Towards Autonomous Emergency Landing for an Optionally Piloted Autogyro." In Vertical Flight Society 71st Annual Forum & Technology Display, 1–15. The Vertical Flight Society, 2015. http://dx.doi.org/10.4050/f-0071-2015-10294.

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In this paper, we present the development of a system for automation of the emergency maneuver for an autogyro after engine power loss. The purpose of the system is to determine a safe and feasible trajectory from the initial condition in forward flight to a final position that is suitable for final approach and landing at a desired location. The flight dynamics of the autogyro is evaluated and a flight control system is developed for the unpowered flight. A simplified dynamic model is created for generation of the gliding trajectory from the starting point to a given final position and ground track, taking into account constant wind values. This model allows us to predict the vertical speed for a given vehicle state and, through optimization, to plan feasible trajectories with minimum altitude loss. Results for generation and tracking of the optimal trajectories are presented, showing good performance and the potential to be used with a sampling-based algorithm for real-time motion planning.
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Hu, Botao, and Sandipan Mishra. "Time-optimal Trajectory Planning for Landing Onto Moving Platforms." In Vertical Flight Society 73rd Annual Forum & Technology Display, 1–9. The Vertical Flight Society, 2017. http://dx.doi.org/10.4050/f-0073-2017-12203.

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In this paper, an algorithm for time-optimal trajectory generation is developed for landing a 6 degree-of-freedom (DOF) quadrotor onto a moving platform (with tilt, heave and pitch). The overall control architecture has a standard guidance-and-tracking control inner-outer loop structure. The outer loop (guidance control) solves the time-optimal trajectory generation problem. Instead of directly solving the time-optimal control problem, the proposed method reformulates this into a nonlinear programming problem that transforms the constraints on the original system dynamics and inputs onto constraints on the system states. This transformation is based on the differential flatness property of the quadrotor dynamics. The proposed method is computationally efficient and can also incorporate the collision avoidance constraints. We further demonstrate that this time-optimal problem can be resolved at periodic intervals (if disturbances and unmodeled dynamics deviate the quadrotor from the optimal trajectory). For the inner loop, a trajectory tracking controller is also designed that can deal with system uncertainties and external disturbances that may affect the quadrotor's dynamics. Simulation and experimental results show the effectiveness of the proposed method.
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Raspaolo, Gennaro, Immacolata Notaro, Luciano Blasi, and Egidio D’Amato. "Optimal Trajectory Planning for UAV Formation Using Theta* and Optimal Control." In 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT), 1369–74. IEEE, 2024. http://dx.doi.org/10.1109/codit62066.2024.10708251.

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Nakamura, Takuma, Stephen Haviland, Dmitry Bershadsky, and Eric Johnson. "Vision Based Optimal Landing On a Moving Platform." In Vertical Flight Society 72nd Annual Forum & Technology Display, 1–11. The Vertical Flight Society, 2016. http://dx.doi.org/10.4050/f-0072-2016-11570.

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This paper describes a vision-based control architecture designed to enable autonomous landing on a moving platform. The landing trajectory is generated by using the receding-horizon differential dynamic programming (DDP), an optimal control method. The trajectory generation is aided by the output of a vision-based target tracking system. The vision system uses multiple extended Kalman filters which allows us to estimate the position and heading of the moving target via the observed locations. The combination of vision-based target tracking system and the receding-horizon DDP gives an unmanned aerial vehicle the capability to adaptively generate a landing trajectory against tracking errors and disturbances. Additionally, by adding the exterior penalty function to the cost of the DDP we can easily constrain the trajectory from collisions and physically infeasible solutions. We provide key mathematics needed for the implementation and share the results of the image-in-the-loop simulation and flight tests to validate the suggested methodology.
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Kehs, Michelle A., Chris Vermillion, and Hosam K. Fathy. "Maximizing Average Power Output of an Airborne Wind Energy Generator Under Parametric Uncertainties." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9764.

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This paper presents a controller for maximizing the time-averaged power output from an airborne wind energy generator in uncertain wind conditions. This system’s optimal energy output often involves flying in periodic figure-8 trajectories, but the precise optimal figure-8 shape is sensitive to environmental conditions, including wind speed. The literature presents controllers that are able to adapt to uncertainties, and this work expands on the current literature by using an extremum seeking based method. Extremum seeking is particularly well-suited for this application because of its well understood stability properties. In this work, extremum seeking is used to search through a family of optimal trajectories (computed offline) that correspond to discrete wind speeds. The controller is efficient in that it only searches for the optimum trajectory over the uncertain parameter (in this paper, wind speed). Results show that the controller converges to the optimal trajectory, provided it is initialized to a stable figure-8. The speed of convergence is dependent on the difference between the initial average power output and the optimal average power output.
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Аnshakov, Gennadiy P., Vadim V. Salmin, Alexey S. Chetverikov, Konstantin V. Peresypkin, and Ivan S. Tkachenko. "Development of method for selecting motion control laws of space optical system on based diffractive membranes during transfer into geostationary orbit." In Information Technology and Nanotechnology-2017. IP Zaitsev V.D., 2017. http://dx.doi.org/10.18287/1613-0073-2017-1966-35-42.

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The article presents a formulation of a problem of trajectory optimization using low-thrust engines for an optical space system based on diffractive membranes. A methodology, where first stage nominal trajectories and control programs are selected and then corrected at the longrange guidance, has been developed for solving the problem of optimizing the trajectories of a flight to a geostationary orbit. At the final stage, algorithms for terminal control are formed, which allows to deliver a cosmic optical system based on diffraction membranes to a given point in the geostationary orbit. The end result is acquisition of Pareto-optimal solutions in the coordinates "characteristic speed-duration of the flight", where each point of the set of solutions has a corresponding a measure of accuracy of payload delivery to a geostationary orbit at a given set of coordinates.
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Zollars, Michael D., and Richard G. Cobb. "Simplex Methods for Optimal Control of Unmanned Aircraft Flight Trajectories." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5031.

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The feasibility of using a constrained Delaunay triangulation method for determining optimal flight trajectories of unmanned air vehicles in a constrained environment is explored. Current methods for developing optimal flight trajectories have yet to achieve computational times that allow for real-time implementation. The proposed method alleviates the dependency of problem specific parameters while eliminating constraints on the Non-Linear Program. Given an input of obstacles with n vertices, a constrained Delaunay triangulation is performed on the space. Converting the vertices of the triangulation to barycentric coordinates on a phased approach defines the state bounds and max time for each phase. With two-dimensional aircraft dynamics, direct orthogonal collocation methods are performed to compute the optimal flight trajectory. Results illustrate computational times and feasibility of Small Unmanned Aircraft System flight trajectories through polygon constraints.
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McIntosh, Kristoff, Jean Reddinger, Sandipan Mishra, and Di Zhao. "Optimal Trajectory Generation for Transitioning Quadrotor Biplane Tailsitter using Differential Flatness." In Vertical Flight Society 77th Annual Forum & Technology Display. The Vertical Flight Society, 2021. http://dx.doi.org/10.4050/f-0077-2021-16858.

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This paper presents the development of an optimization-based trajectory planner for the autonomous transition of a quadrotor biplane tailsitter (QRBP) between the flight modes of hover to forward flight and forward flight to hover. The trajectory planner is formulated as an optimization problem with an embedded dynamic model of the QRBP, vehicle design constraints (e.g. power), physical constraints (e.g. stall) and initial/terminal states for the transition. A differentially flat reformulation is employed to reduce the computational cost of the trajectory planner for on-board mission planning. The solution of this problem yields time-optimal state and input trajectories for transition. Using this trajectory planner, we generate trajectories for various transition flight missions (from hover to forward flight and vice versa) under various constraints. Further, we demonstrate how the proposed algorithm can also be used to assess the agility of a vehicle in terms of minimum space required to perform a specific maneuver or transition, given physical design constraints (such as maximum power). Finally, we demonstrate trajectory tracking on a high fidelity simulation of a QRBP with a cascaded dynamic-inversion based controller with a control blending strategy between the quadcopter and forward-flight control modes, for hover to forward flight.
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9

Liu, Longxi, Zihao Wang, Yunqing Zhang, and Jinglai Wu. "Trajectory Planning of Autonomous Vehicles Based on Parameterized Control Optimization for Three-Degree-of-Freedom Vehicle Dynamics Model." In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2024. http://dx.doi.org/10.4271/2024-01-2332.

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<div class="section abstract"><div class="htmlview paragraph">In contemporary trajectory planning research, it is common to rely on point-mass model for trajectory planning. However, this often leads to the generation of trajectories that do not adhere to the vehicle dynamics, thereby increasing the complexity of trajectory tracking control. This paper proposes a local trajectory planning algorithm that combines sampling and sequential quadratic optimization, considering the vehicle dynamics model. Initially, the vehicle trajectory is characterized by utilizing vehicle dynamic control variables, including the front wheel angle and the longitudinal speed. Next, a cluster of sampling points for the anticipated point corresponding to the current vehicle position is obtained through a sampling algorithm based on the vehicle's current state. Then, the trajectory planning problem between these two points is modeled as a sequential quadratic optimization problem. By employing an offline method, the optimal trajectory set between the present position and the anticipated point cluster is computed. After acquiring clusters of candidate trajectories, each candidate trajectory is evaluated to determine its feasibility and cost, considering factors such as efficiency and comfort. The best trajectory is then chosen as the local trajectory of vehicle. The trajectories generated using the proposed method and the quintic polynomial method are both tracked and controlled using a 3-DOF vehicle dynamic model. The results clearly demonstrate that the trajectories generated by the proposed method exhibit superior tracking performance.</div></div>
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10

Ennasr, Osama, Giorgos Mamakoukas, Todd Murphey, and Xiaobo Tan. "Ergodic Exploration for Adaptive Sampling of Water Columns Using Gliding Robotic Fish." In ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/dscc2018-9179.

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In recent years, gliding robotic fish have emerged as promising mobile platforms for underwater sensing and monitoring due to their notable energy efficiency and maneuverability. For sensing of aquatic environments, it is important to use efficient sampling strategies that incorporate previously observed data in deciding where to sample next so that the gained information is maximized. In this paper, we present an adaptive sampling strategy for mapping a scalar field in an underwater environment using a gliding robotic fish. An ergodic exploration framework is employed to compute optimal exploration trajectories. To effectively deal with the challenging complexity of finding optimum three-dimensional trajectories that are feasible for the gliding robotic fish, we propose a novel strategy that combines a unicycle model-based 2D trajectory optimization with spiral-enabled water column sampling. Gaussian process (GP) regression is used to infer the field values at unsampled locations, and to update a map of expected information density (EID) in the environment. The outputs of GP regression are then fed back to the ergodic exploration engine for trajectory optimization. We validate the proposed approach with simulation results and compare its performance with a uniform sampling grid.
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