The minimum-time for a robot arm has been a longstanding and unsolved problem of considerable interest. We present a general solution to this problem that involves joint-space tesselation, a dynamic time-scaling algorithm, and graph search. The solution incorporates full dynamics of movement and actuator constraints, and can be easily extended for joint limits and work space obstacles, but is subject to the particular tesselation scheme used. The results presented show that, in general the optimal paths are not straight lines, bit rather curves in joint-space that utilize the dynamics of the arm and gravity to help in moving the arm faster to its destination. Implementation difficulties due to the tesselation and to combinatorial proliferation of paths are discussed.

Cette thèse se compose de deux parties. Dans la première partie, nous étudions les stratégies de temps minimum pour le traitement de la pollution dans de grandes ressources en eau, par exemple des lacs ou réservoirs naturels, à l'aide d'un bioréacteur continu qui fonctionne à un état quasi stationnaire. On contrôle le débit d'entrée d'eau au bioréacteur, dont la sortie revient à la ressource avec le même débit. Nous disposons de l'hypothèse d'homogénéité de la concentration de polluant dans la ressource en proposant trois modèles spatialement structurés. Le premier modèle considère deux zones connectées l'une à l'autre par diffusion et seulement une d'entre elles connectée au bioréacteur. Avec l'aide du Principe du Maximum de Pontryagin, nous montrons que le contrôle optimal en boucle fermée dépend seulement des mesures de pollution dans la zone traitée, sans influence des paramètres de volume, diffusion, ou la concentration dans la zone non traitée. Nous montrons que l'effet d'une pompe de recirculation qui aide à homogénéiser les deux zones est avantageux si opérée à vitesse maximale. Nous prouvons que la famille de fonctions de temps minimal en fonction du paramètre de diffusion est décroissante. Le deuxième modèle consiste en deux zones connectées l'une à l'autre par diffusion et les deux connectées au bioréacteur. Ceci est un problème dont l'ensemble des vitesses est non convexe, pour lequel il n'est pas possible de prouver directement l'existence des solutions. Nous surmontons cette difficulté et résolvons entièrement le problème étudié en appliquant le principe de Pontryagin au problème de contrôle relaxé associé, obtenant un contrôle en boucle fermée qui traite la zone la plus polluée jusqu'au l'homogénéisation des deux concentrations. Nous obtenons des limites explicites sur la fonction valeur via des techniques de Hamilton-Jacobi-Bellman. Nous prouvons que la fonction de temps minimal est non monotone par rapport au paramètre de diffusion. Le troisième modèle consiste en deux zones connectées au bioréacteur en série et une pompe de recirculation entre elles. L'ensemble des contrôles dépend de l'état, et nous montrons que la contrainte est active à partir d'un temps jusqu'à la fin du processus. Nous montrons que le contrôle optimal consiste à l'atteinte d'un temps à partir duquel il est optimal de recirculer à vitesse maximale et ensuite ré-polluer la deuxième zone avec la concentration de la première. Ce résultat est non intuitif. Des simulations numériques illustrent les résultats théoriques, et les stratégies optimales obtenues sont testées sur des modèles hydrodynamiques, en montrant qu'elles sont de bonnes approximations de la solution du problème inhomogène. La deuxième partie consiste au développement et l'étude d'un modèle stochastique de réacteur biologique séquentiel. Le modèle est obtenu comme une limite des processus de naissance et de mort. Nous établissons l'existence et l'unicité des solutions de l'équation contrôlée qui ne satisfait pas les hypothèses habituelles. Nous prouvons que pour n'importe quelle loi de contrôle la probabilité d'extinction de la biomasse est positive. Nous étudions le problème de la maximisation de la probabilité d'atteindre un niveau de pollution cible, avec le réacteur à sa capacité maximale, avant l'extinction. Ce problème ne satisfait aucune des suppositions habituelles (la dynamique n'est pas lipschitzienne, diffusion dégénérée localement hölderienne, contraintes d'état, ensembles cible et absorbant s'intersectent), donc le problème doit être étudié dans deux étapes: en premier lieu, nous prouvons la continuité de la fonction de coût non contrôlée pour les conditions initiales avec le volume maximal et ensuite nous développons un principe de programmation dynamique pour une modification du problème original comme un problème de contrôle optimal avec coût final sans contrainte sur l'état. / This thesis consists of two parts. In the first part we study minimal time strategies for the treatment of pollution in large water volumes, such as lakes or natural reservoirs, using a single continuous bioreactor that operates in a quasi-steady state. The control consists of feeding the bioreactor from the resource, with clean output returning to the resource with the same flow rate. We drop the hypothesis of homogeneity of the pollutant concentration in the water resource by proposing three spatially structured models. The first model considers two zones connected to each other by diffusion and only one of them treated by the bioreactor. With the help of the Pontryagin Maximum Principle, we show that the optimal state feedback depends only on the measurements of pollution in the treated zone, with no influence of volume, diffusion parameter, or pollutant concentration in the untreated zone. We show that the effect of a recirculation pump that helps to mix the two zones is beneficial if operated at full speed. We prove that the family of minimal time functions depending on the diffusion parameter is decreasing. The second model consists of two zones connected to each other by diffusion and each of them connected to the bioreactor. This is a problem with a non convex velocity set for which it is not possible to directly prove the existence of its solutions. We overcome this difficulty and fully solve the studied problem applying Pontryagin's principle to the associated problem with relaxed controls, obtaining a feedback control that treats the most polluted zone up to the homogenization of the two concentrations. We also obtain explicit bounds on its value function via Hamilton-Jacobi-Bellman techniques. We prove that the minimal time function is nonmonotone as a function of the diffusion parameter. The third model consists of a system of two zones connected to the bioreactor in series, and a recirculation pump between them. The control set depends on the state variable; we show that this constraint is active from some time up to the final time. We show that the optimal control consists of waiting up to a time from which it is optimal the mixing at maximum speed, and then to repollute the second zone with the concentration of the first zone. This is a non intuitive result. Numerical simulations illustrate the theoretical results, and the obtained optimal strategies are tested in hydrodynamic models, showing to be good approximations of the solution of the inhomogeneous problem. The second part consists of the development and study of a stochastic model of sequencing batch reactor. We obtain the model as a limit of birth and death processes. We establish the existence and uniqueness of solutions of the controlled equation that does not satisfy the usual assumptions. We prove that with any control law the probability of extinction is positive, which is a non classical result. We study the problem of the maximization of the probability of attaining a target pollution level, with the reactor at maximum capacity, prior to extinction. This problem does not satisfy any of the usual assumptions (non Lipschitz dynamics, degenerate locally H"older diffusion parameter, restricted state space, intersecting reach and avoid sets), so the problem must be studied in two stages: first, we prove the continuity of the uncontrolled cost function for initial conditions with maximum volume, and then we develop a dynamic programming principle for a modification of the problem as an optimal control problem with final cost and without state constraint.

O problema de transferir uma carga ao se movimentar num plano em tempo mínimo e sem oscilação no ponto de descarga, num guindaste portuário tipo pórtico é investigado neste trabalho. Assume-se que a carga esteja inicialmente em repouso na posição vertical no ponto de carga acima do navio e igualmente em repouso no ponto de descarga na moega de alimentação no porto. Assume-se também que o carro do guindaste esteja em repouso em ambos os pontos. Um modelo completo é apresentado para o sistema do guindaste onde as equações dinâmicas não-lineares são linearizadas para ângulos de oscilação pequenos o suficiente e reescritas para a forma adimensional. A solução de tempo mínimo é buscada considerando como variáveis de controle as funções do tempo que descrevem tanto a força aplicada no carro para produzir seu deslocamento horizontal, como a velocidade de içamento da carga. Um método iterativo preditor-corretor usando a Programação Linear (PL) é proposto, baseado no modelo do sistema de tempo discreto onde as variáveis de controle são tomadas constantes por trechos. Na etapa corretora, assume-se que o movimento de içamento é dado e uma solução de tempo mínimo é obtida resolvendo-se uma seqüência de problemas de PL de tempo fixo e máximo deslocamento. Na etapa preditora, um modelo linearizado é empregado para obter-se uma correção ótima do movimento de içamento usando a PL. O problema de controle de tempo mínimo é formulado levando-se em consideração restrições práticas na velocidade do carro do guindaste, velocidade máxima de içamento, assim como na máxima força que pode ser aplicada ao carro. Resultados numéricos são apresentados e mostram a efetividade do método. / The problem of minimum-time anti-swing transfer of a load in a ship-to-pier gantry crane is investigated in this work. The load is assumed to be initially at rest at the vertical position at the loading point above the ship and equally at rest at the unloading point above the hopper. The trolley is also assumed to be at rest at both points. A complete model is presented for the crane system where the nonlinear dynamic equations are linearized for sufficiently small swing angles and then rewritten in dimensionless form. The minimum-time solution is sought by considering as control variables both the force applied on the trolley that produces its horizontal motion and the hoisting speed of the load as functions of time. A predictor-corrector iterative method using Linear Programming (LP) is proposed based on a discretetime model of the system where the control variables are taken as stepwise constants. At the corrector step, the hoisting motion is assumed given and a minimum-time solution is obtained by solving a sequence of LP problems representing fixed-time maximum-range problems. At the predictor step, a linearized model is employed to obtain an optimal correction of the hoisting motion using LP. The minimum-time control problem is formulated by taking into account practical constraints on the maximum speeds of both the trolley and the load hoisting, as well as on the maximum force that can be applied to the trolley. Numerical results are presented and show the effectiveness of the method.

This thesis addresses the challenges in the efficient and robust generation and optimization of three-dimensional landing trajectories for fixed-wing aircraft subject to prescribed boundary conditions and constraints on maneuverability and collision avoidance. In particular, this thesis focuses on the airliner emergency landing scenario and the minimization of landing time. The main contribution of the thesis is two-fold. First, it provides a hierarchical scheme for integrating the complementary strength of a variety of methods in path planning and trajectory optimization for the improvement in efficiency and robustness of the overall landing trajectory optimization algorithm. The second contribution is the development of new techniques and results in mesh refinement for numerical optimal control, optimal path tracking, and smooth path generation, which are all integrated in a hierarchical scheme and applied to the landing trajectory optimization problem. A density function based grid generation method is developed for the mesh refinement process during numerical optimal control. A numerical algorithm is developed based on this technique for solving general optimal control problems, and is used for optimizing aircraft landing trajectories. A path smoothing technique is proposed for recovering feasibility of the path and improving the tracking performance by modifying the path geometry. The optimal aircraft path tracking problem is studied and analytical results are presented for both the minimum-time, and minimum-energy tracking with fixed time of arrival. The path smoothing and optimal path tracking methods work together with the geometric path planner to provide a set of feasible initial guess to the numerical optimal control algorithm. The trajectory optimization algorithm in this thesis was tested by simulation experiments using flight data from two previous airliner accidents under emergency landing scenarios.The real-time application of the landing trajectory optimization algorithm as part of the aircraft on-board automation avionics system has the potential to provide effective guidelines to the pilots for improving the fuel consumption during normal landing process, and help enhancing flight safety under emergency landing scenarios. The proposed algorithms can also help design optimal take-off and landing trajectories and procedures for airports.

abstract: Toward the ambitious long-term goal of a fleet of cooperating Flexible Autonomous Machines operating in an uncertain Environment (FAME), this thesis addresses various control objectives for ground vehicles. There are two main objectives within this thesis, first is the use of visual information to control a Differential-Drive Thunder Tumbler (DDTT) mobile robot and second is the solution to a minimum time optimal control problem for the robot around a racetrack. One method to do the first objective is by using the Position Based Visual Servoing (PBVS) approach in which a camera looks at a target and the position of the target with respect to the camera is estimated; once this is done the robot can drive towards a desired position (x_ref, z_ref). Another method is called Image Based Visual Servoing (IBVS), in which the pixel coordinates (u,v) of markers/dots placed on an object are driven towards the desired pixel coordinates (u_ref, v_ref) of the corresponding markers. By doing this, the mobile robot gets closer to a desired pose (x_ref, z_ref, theta_ref). For the second objective, a camera-based and noncamera-based (v,theta) cruise-control systems are used for the solution of the minimum time problem. To set up the minimum time problem, optimal control theory is used. Then a direct method is implemented by discretizing states and controls of the system. Finally, the solution is obtained by modeling the problem in AMPL and submitting to the nonlinear optimization solver KNITRO. Simulation and experimental results are presented. The DDTT-vehicle used within this thesis has different components as summarized below: (1) magnetic wheel-encoders/IMU for inner-loop speed-control and outer-loop directional control, (2) Arduino Uno microcontroller-board for encoder-based inner-loop speed-control and encoder-IMU-based outer-loop cruise-directional-control, (3) Arduino motor-shield for inner-loop speed-control, (4) Raspberry Pi II computer-board for outer-loop vision-based cruise-position-directional-control, (5) Raspberry Pi 5MP camera for outer-loop cruise-position-directional control. Hardware demonstrations shown in this thesis are summarized: (1) PBVS without pan camera, (2) PBVS with pan camera, (3) IBVS with 1 marker/dot, (4) IBVS with 2 markers, (5) IBVS with 3 markers, (6) camera and (7) noncamera-based (v,theta) cruise control system for the minimum time problem. / Dissertation/Thesis / Masters Thesis Electrical Engineering 2016

O problema de transferir uma carga ao se movimentar num plano em tempo mínimo e sem oscilação no ponto de descarga, num guindaste portuário tipo pórtico é investigado neste trabalho. Assume-se que a carga esteja inicialmente em repouso na posição vertical no ponto de carga acima do navio e igualmente em repouso no ponto de descarga na moega de alimentação no porto. Assume-se também que o carro do guindaste esteja em repouso em ambos os pontos. Um modelo completo é apresentado para o sistema do guindaste onde as equações dinâmicas não-lineares são linearizadas para ângulos de oscilação pequenos o suficiente e reescritas para a forma adimensional. A solução de tempo mínimo é buscada considerando como variáveis de controle as funções do tempo que descrevem tanto a força aplicada no carro para produzir seu deslocamento horizontal, como a velocidade de içamento da carga. Um método iterativo preditor-corretor usando a Programação Linear (PL) é proposto, baseado no modelo do sistema de tempo discreto onde as variáveis de controle são tomadas constantes por trechos. Na etapa corretora, assume-se que o movimento de içamento é dado e uma solução de tempo mínimo é obtida resolvendo-se uma seqüência de problemas de PL de tempo fixo e máximo deslocamento. Na etapa preditora, um modelo linearizado é empregado para obter-se uma correção ótima do movimento de içamento usando a PL. O problema de controle de tempo mínimo é formulado levando-se em consideração restrições práticas na velocidade do carro do guindaste, velocidade máxima de içamento, assim como na máxima força que pode ser aplicada ao carro. Resultados numéricos são apresentados e mostram a efetividade do método. / The problem of minimum-time anti-swing transfer of a load in a ship-to-pier gantry crane is investigated in this work. The load is assumed to be initially at rest at the vertical position at the loading point above the ship and equally at rest at the unloading point above the hopper. The trolley is also assumed to be at rest at both points. A complete model is presented for the crane system where the nonlinear dynamic equations are linearized for sufficiently small swing angles and then rewritten in dimensionless form. The minimum-time solution is sought by considering as control variables both the force applied on the trolley that produces its horizontal motion and the hoisting speed of the load as functions of time. A predictor-corrector iterative method using Linear Programming (LP) is proposed based on a discretetime model of the system where the control variables are taken as stepwise constants. At the corrector step, the hoisting motion is assumed given and a minimum-time solution is obtained by solving a sequence of LP problems representing fixed-time maximum-range problems. At the predictor step, a linearized model is employed to obtain an optimal correction of the hoisting motion using LP. The minimum-time control problem is formulated by taking into account practical constraints on the maximum speeds of both the trolley and the load hoisting, as well as on the maximum force that can be applied to the trolley. Numerical results are presented and show the effectiveness of the method.

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The main body of this thesis consists of six appended papers. In the  first two, different  cooperative surveillance problems are considered. The second two consider different aspects of the trajectory planning problem, while the last two deal with observer design for mobile robotic and Euler-Lagrange systems respectively.In Papers A and B,  a combinatorial optimization based framework to cooperative surveillance missions using multiple Unmanned Ground Vehicles (UGVs) is proposed. In particular, Paper A  considers the the Minimum Time UGV Surveillance Problem (MTUSP) while Paper B treats the Connectivity Constrained UGV Surveillance Problem (CUSP). The minimum time formulation is the following. Given a set of surveillance UGVs and a polyhedral area, find waypoint-paths for all UGVs such that every point of the area is visible from  a point on a waypoint-path and such that the time for executing the search in parallel is minimized.  The connectivity constrained formulation  extends the MTUSP by additionally requiring the induced information graph to be  kept recurrently connected  at the time instants when the UGVs  perform the surveillance mission.  In these two papers, the NP-hardness of  both these problems are shown and decomposition techniques are proposed that allow us to find an approximative solution efficiently in an algorithmic manner.Paper C addresses the problem of designing a real time, high performance trajectory planner for an aerial vehicle that uses information about terrain and enemy threats, to fly low and avoid radar exposure on the way to a given target. The high-level framework augments Receding Horizon Control (RHC) with a graph based terminal cost that captures the global characteristics of the environment.  An important issue with RHC is to make sure that the greedy, short term optimization does not lead to long term problems, which in our case boils down to two things: not getting into situations where a collision is unavoidable, and making sure that the destination is actually reached. Hence, the main contribution of this paper is to present a trajectory planner with provable safety and task completion properties. Direct methods for trajectory optimization are traditionally based on a priori temporal discretization and collocation methods. In Paper D, the problem of adaptive node distribution is formulated as a constrained optimization problem, which is to be included in the underlying nonlinear mathematical programming problem. The benefits of utilizing the suggested method for  online  trajectory optimization are illustrated by a missile guidance example.In Paper E, the problem of active observer design for an important class of non-uniformly observable systems, namely mobile robotic systems, is considered. The set of feasible configurations and the set of output flow equivalent states are defined. It is shown that the inter-relation between these two sets may serve as the basis for design of active observers. The proposed observer design methodology is illustrated by considering a  unicycle robot model, equipped with a set of range-measuring sensors. Finally, in Paper F, a geometrically intrinsic observer for Euler-Lagrange systems is defined and analyzed. This observer is a generalization of the observer proposed by Aghannan and Rouchon. Their contractivity result is reproduced and complemented  by  a proof  that the region of contraction is infinitely thin. Moreover, assuming a priori bounds on the velocities, convergence of the observer is shown by means of Lyapunov's direct method in the case of configuration manifolds with constant curvature. / QC 20100622 / TAIS, AURES