This dissertation focuses on constrained control of two applications: helicopter and ocean current turbines (OCT). A major contribution in the helicopter application is a novel model predictive control (MPC) framework for helicopter shipboard operations in high demanding sea-based conditions. A complex helicopter-ship dynamics interface has been developed as a system of implicit nonlinear ordinary differential equations to capture essential characteristics of the nonlinear helicopter dynamics, the ship dynamics, and the ship airwake interactions. Various airwake models such as Control Equivalent Turbulence Inputs (CETI) model and Computation Fluid Dynamics (CFD) data of the airwake are incorporated in the interface to describe a realistic model of the shipborne helicopter. The feasibility of the MPC design is investigated using two case studies: automatic deck landing during the ship quiescent period in sea state 5, and lateral reposition toward the ship in different wind-over-deck conditions. To improve the overall MPC performance, an updating scheme for the internal model of the MPC is proposed using linearization around operating points. A mixed-integer MPC algorithm is also developed for helicopter precision landing on moving decks. The performance of this control structure is evaluated via numerical simulations of the automatic deck landing in adverse conditions such as landing on up-stroke, and down-stroke moving decks with high energy indices. Kino-dynamic motion planning for coordinated maneuvers to satisfy the helicopter-ship rendezvous conditions is implemented via mixed integer quadratic programming. In the OCT application, the major contribution is that a new idea is leveraged from helicopter blade control by introducing cyclic blade pitch control in OCT. A minimum energy, constrained control method, namely Output Variance Constrained (OVC) control is studied for OCT flight control in the presence of external disturbances. The minimum achievable output variance bounds are also computed and a parametric study of design parameters is conducted to evaluate their influence on the OVC performance. The performance of the OVC control method is evaluated both on the linear and nonlinear OCT models. Furthermore, control design for the OCT with sensor failures is also examined. Lastly, the MPC strategy is also investigated to improve the OCT flight control performance in simultaneous satisfaction of multiple constraints and to avoid blade stall. / Ph. D.

Dans la plupart des problèmes de synthèse, la loi de commande obtenue doit répondre simultanément à des critères réquentiels et temporels en vue de satisfaire un cahier des charges précis. Les derniers développements des techniques de synthèse Hinf de contrôleurs structurés permettent d'obtenir des lois de commande satisfaisant des critères fréquentiels multiples. En revanche, la synthèse de loi de commande satisfaisant une contrainte temporelle sur une sortie ou un état du système est plus complexe. Dans ce travail de thèse, la technique OIST est considérée pour ce type de contraintes. Elle consiste à saturer la sortie du contrôleur dès que la contrainte n'est plus vérifiée afin de restreindre l'ensemble des sorties admissibles. Initialement formulée pour les systèmes linéaires connus dont l'état est mesuré, la technique OIST peut être généralisée pour permettre de considérer des systèmes incertains. C'est l'extension OISTeR qui est proposée dans ce travail. Elle utilise les données d'un observateur par intervalles pour borner de manière garantie le vecteur d'état. La théorie des observateurs par intervalles a récemment fait l'objet de nombreux travaux. La méthode la plus rapide pour obtenir un observateur par intervalles d'un système donné est de considérer un système intermédiaire coopératif dans de nouvelles coordonnées. Une nouvelle technique de détermination de ces nouvelles coordonnées, intitulée SCorplO, est proposée dans ce mémoire. L'ensemble des techniques présentées est appliqué au contrôle d'un lanceur flexible durant son vol atmosphérique, en présence de rafales de vent et sous contrainte temporelle sur l'angle d'incidence. / Ln control design problems, both frequency- and time-domain requirements are usually considered such that the resulting control law satisfies the specifications. Novel non-smooth optimization techniques can be used to achieve multiple frequency-domain specifications over a family of linear models. However, enforcing time-domain constraints on a given output or state is more challenging Since translating them into frequency-domain requirements may be inaccurate. This motivates the study of an additional approach to the Hinf control design techniques. When time-domain constraints are satisfied, the nominal control law reduces to a controller satisfying the frequency-domain constraints. Upon violation of the ime-domain constraint, an additional tool named OIST is used to saturate the controller output so as to restrict the reachable set of the constrained system output. Stability guarantees are obtained for minimum phase systems. Further developments proposed therein allow the consideration of uncertain systems With incomplete state measurements. This is he OISTeR approach. The method uses certified bounds on the considered system state as provided by an interval observer. he theory of interval observers is well-established. ln the case of linear systems, the most common approach is to consider an intermediate cooperative system on which the interval observer can be built. The novel SCorplO design method proposed in this work is used to compute such cooperative representation. ln this thesis, the considered application is the atmospheric control of a flexible launch vehicle under a time-domain constraint on the angle of attack and in the presence of wind gusts.

The main interest of the present thesis is the constrained control of time-delay system, more specifically taking into consideration the discretization problem (due to, for example, a communication network) and the presence of constraints in the system's trajectories and control inputs. The effects of data-sampling and modeling problem are studied in detail, where an uncertainty is added into the system due to additional effect of the discretization and delay. The delay variation with respect to the sampling instants is characterized by a polytopic supra-approximation of the discretization/delay induced uncertainty. Some stabilizing techniques, based on Lyapunov's theory, are then derived for the unconstrained case. Lyapunov-Krasovskii candidates were also used to obtain LMI conditions for a state feedback, in the ''original" state-space of the system. For the constrained control purposes, the set invariance theory is used intensively, in order to obtain a region where the system is ''well-behaviored", despite the presence of constraints and (time-varying) delay. Due to the high complexity of the maximal delayed state admissible set obtained in the augmented state-space approach, in the present manuscript we proposed the concept of set invariance in the ''original" state-space of the system, called D-invariance. Finally, in the las part of the thesis, the MPC scheme is presented, in order to take into account the constraints and the optimality of the control solution.

This master´s thesis deals with control of unstable processes with two unstable complex poles using algebraic control with emphasis in value of the controller output. Thesis consists of theoretical introduction, including initial conditions with analysis of basic approaches to the control design with one or two degrees of freedom regulators by solving polynomial equations. Constrained control is studied more detailed. Optimization problem of „lowest fuel consumption“ is used for design of controller and is used for both degrees of freedom regulators with additional condition of zero variance control. Thesis includes some examples of control design by described method. Small library of MatLab functions were developed also to make the design more easier. Conclusions are made at the end and achieved goals are reviewed.

L’objet de cette thèse est l’étude des jeux champs moyen déterministes avec contrainte sur l’état. La théorie des jeux à champ moyen (mean field games (MFG)), initiée par Lasry et Lions en 2006, étudie des problèmes d’optimisation pour grandes populations d'agents dans un milieu dynamique. L'analyse mathématique de tels problèmes s'est jusqu'à présent concentrée sur des situations dans lequel les agents évoluent dans tout l’espace. En pratique, cependant, les agents ont des contraintes sur l'état. Le but de la thèse est celle d'étudier l'impact de ces contraintes sur l'analyse des systèmes de jeux à champ moyen. Nous montrons que les équilibres de Nash peuvent être décrits en termes de point fixe sur un espace de mesure sur des courbes contraintes (notion d’équilibre généralisé). Afin d’obtenir des résultats plus fins sur de tels équilibres, nous montrons un principe d’optimalité lisse pour les courbes optimales avec contraintes sur l’état. Nous en déduisons que les équilibres généralisés satisfont un système MFG, où les équations de Hamiton-Jacobi et les équations de transport doivent être entendues dans un sens spécifique. / The aim of this Thesis is to study deterministic mean field games with state constraints. Mean field games (MFG) is a recent theory invented by Lasry and Lions which studies optimization problems with large populations of agents in a dynamical framework. The mathematical analysis of such problems has so far focused on situations where the agents can evolve in the whole space. In practice, however, the agents often have constraints on their state. The aim of this Thesis is to understand the consequence of such constraints on the analysis of mean field games. We first show that the Nash MFG equilibria can be described as fixed points on the space of measures on constrained trajectories (generalized MFG equilibria). In order to obtain more precise results on these equilibria, we show a smooth optimality principle for the optimal trajectories of control problem with state constraints. We derive from this that the generalized equilibria satisfy a MFG system in which the Hamilton-Jacobi equation and the continuity equation have to be understand in a specific sense.

This thesis focuses on vision-based detection and observation of small, slow-moving targets using a gimballed fixed-wing unmanned aircraft system (UAS). Generally, visual tracking algorithms are tuned to detect motion of relatively large objects in the scene with noticeably significant motion; therefore, applications such as high-altitude visual searches for human motion often ignore target motion as noise. Furthermore, after a target is identified, arbitrary maneuvers for transitioning to overhead orbits for better observation may result in temporary or permanent loss of target visibility. We present guidelines for tuning parameters of the Visual Multiple Target Tracking (Visual MTT) algorithm to enhance its detection capabilities for very small, slow-moving targets in high-resolution images. We show that the tuning approach is able to detect walking motion of a human described by 10-15 pixels from high altitudes. An algorithm is then presented for defining rotational bounds on the controllable degrees of freedom of an aircraft and gimballed camera system for maintaining visibility of a known ground target. Critical rotations associated with the fastest loss or acquisition of target visibility are also defined. The accuracy of these bounds are demonstrated in simulation and simple applications of the algorithm are described for UAS. We also present a path planning and control framework for defining and following both dynamically and visually feasibly transition trajectories from an arbitrary point to an orbit over a known target for further observation. We demonstrate the effectiveness of this framework in maintaining constant target visibility while transitioning to the intended orbit as well as in transitioning to a lower altitude orbit for more detailed visual analysis of the intended target.

La première partie de la thèse est consacrée à la commande avec contraintes de systèmes différentiellement plats. Deux types de systèmes sont étudiés : les systèmes non linéaires de dimension finie et les systèmes linéaires à retards. Nous présentons une approche unifiée pour intégrer les contraintes d'entrée/état/sortie dans la planification des trajectoires. Pour cela, nous spécialisons les sorties plates (ou les trajectoires de référence) sous forme de courbes de Bézier. En utilisant la propriété de platitude, les entrées/états du système peuvent être exprimés sous la forme d'une combinaison de sorties plates (courbes de Bézier) et de leurs dérivées. Par conséquent, nous obtenons explicitement les expressions des points de contrôle des courbes de Bézier d'entrées/états comme une combinaison des points de contrôle des sorties plates. En appliquant les contraintes souhaitées à ces derniers points de contrôle, nous trouvons les régions faisables pour les points de contrôle de Bézier de sortie, c'est-à-dire un ensemble de trajectoires de référence faisables. Ce cadre permet d’éviter le recours, en général fort coûteux d’un point de vue informatique, aux schémas d’optimisation. Pour résoudre les incertitudes liées à l'imprécision de l'identification et modélisation des modèles et les perturbations, nous utilisons la commande sans modèle (Model Free Control-MFC) et dans la deuxième partie de la thèse, nous présentons deux applications démontrant l'efficacité de notre approche : 1. Nous proposons une conception de contrôleur qui évite les procédures d'identification du système du quadrotor tout en restant robuste par rapport aux perturbations endogènes (la performance de contrôle est indépendante de tout changement de masse, inertie, effets gyroscopiques ou aérodynamiques) et aux perturbations exogènes (vent, bruit de mesure). Pour atteindre notre objectif en se basant sur la structure en cascade d'un quadrotor, nous divisons le système en deux sous-systèmes de position et d'attitude contrôlés chacun indépendamment par la commande sans modèle de deuxième ordre dynamique. Nous validons notre approche de contrôle avec trois scénarios réalistes : en présence d'un bruit inconnu, en présence d’un vent variant dans le temps et en présence des variations inconnues de masse, tout en suivant des manœuvres agressives. 2. Nous utilisons la commande sans modèle et les correcteurs « intelligents » associés, pour contrôler (maintenir) l'élasticité horizontale d'un système de Cloud Computing. Comparée aux algorithmes commerciaux d’Auto-Scaling, notre approche facilement implémentable se comporte mieux, même avec de fluctuations aigües de charge. Ceci est confirmé par des expériences sur le cloud public Amazon Web Services (AWS). / The first part of the thesis is devoted to the control of differentially flat systems with constraints. Two types of systems are studied: non-linear finite dimensional systems and linear time-delay systems. We present an approach to embed the input/state/output constraints in a unified manner into the trajectory design for differentially flat systems. To that purpose, we specialize the flat outputs (or the reference trajectories) as Bézier curves. Using the flatness property, the system’s inputs/states can be expressed as a combination of Bézier curved flat outputs and their derivatives. Consequently, we explicitly obtain the expressions of the control points of the inputs/states Bézier curves as a combination of the control points of the flat outputs. By applying desired constraints to the latter control points, we find the feasible regions for the output Bézier control points i.e. a set of feasible reference trajectories. This framework avoids the use of generally high computing cost optimization schemes.    To resolve the uncertainties arising from imprecise model identification and the unknown pertubations, we employ the Model-Free Control (MFC) and in the second part of the thesis we present two applications demonstrating the effectiveness of our approach: 1. We propose a controller design that avoids the quadrotor’s system identification procedures while staying robust with respect to the endogenous (the control performance is independent of any mass change, inertia, gyroscopic or aerodynamic effects) and exogenous disturbances (wind, measurement noise). To reach our goal, based on the cascaded structure of a quadrotor, we divide the system into positional and attitude subsystems each controlled by an independent Model-Free controller of second order dynamics. We validate our control approach in three realistic scenarios: in presence of unknown measurement noise, with unknown time-varying wind disturbances and mass variation while tracking aggressive manoeuvres. 2. We employ the Model-Free Control to control (maintain) the “horizontal elasticity” of a Cloud Computing system. When compared to the commercial “Auto-Scaling” algorithms, our easily implementable approach behaves better, even with sharp workload fluctuations. This is confirmed by experiments on the Amazon Web Services (AWS) public cloud.

No description available.

In this thesis, we develop methods leading towards the distributed control of spatio-temporally constrained systems. Overall, we focus on two different approaches: a model predictive control approach and an approach based on ensuring set-invariance via control barrier functions. Developing a distributed control framework for spatio-temporally constrained systems is challenging since multiple subsystems are interconnected via time-varying state constraints. Often, such constraints are only implicitly given as logic formulas, for example in Signal Temporal Logic (STL). Our approach to dealing with spatio-temporal constraints is as follows. We aim at combining the computational efficiency of low-level feedback controllers with planning algorithms. Low-level feedback controllers shall ensure the satisfaction of parts of spatio-temporal constraints such as coupling state constraints or short term time-constraints. In contrast, planning algorithms account for those parts that require computationally intense planning operations. Powerful low-level controllers can simplify the planning task significantly. For this reason, the focus of this thesis is on the development of low level feedback controllers.  In the first part, we focus on handling coupling state constraints using a model predictive control (MPC) approach. Commonly, the distributed handling of coupling state constraints requires a sequential or iterative MPC scheme which however is computationally time-intense. We address this issue by employing consistency constraints to develop a parallelized distributed model predictive controller (DMPC). By using consistency constraints, each subsystem guarantees to its neighbors that its states stay within a particular neighborhood around a reference trajectory. Furthermore, we propose extensions to robust and iterative schemes. Building up on this, also systems with bounded dynamic couplings can be controlled. In the second part, we focus on methods for ensuring set-invariance. In particular, we focus on control barrier functions (CBF). We show how spatio-temporal constraints that comprise disjunctions (logic OR) can be encoded in non-smooth time-varying control barrier functions and how subgradients can be used to synthesize an efficient gradient-based controller. For these results, controllability assumptions must be invoked. To extend the results to systems with weaker controllability properties, we investigate the connection between controllability properties and the construction of CBFs. As a result, we propose a construction method for CBFs based on finite horizon predictions. The constructed CBF exhibits favorable properties for the extension of the previous results on encoding spatio-temporal constraints in CBFs to systems with weaker controllability properties. At last, we investigate with a case study how set-invariance methods can be used to implicitly coordinate systems subject to coupled state constraints. Our proposed method is fully decentralized and subsystems coordinate themselves purely via their actions and the adjustment of their individual constraints. In the end, we draw a conclusion and outline how the presented results contribute to the development of a distributed control framework for spatio-temporally constrained systems. / I den här avhandlingen utvecklar vi metoder som leder till distribuerad styrning av tillstånds-temporalt begränsade system. Vi följer två olika tillvägagångssätt: å ena sidan en modellprediktiv styrning och å andra sidan ett tillvägagångssätt som bygger på att säkerställa invarians i mängden via kontrollbarriärfunktioner. Det är en utmaning att utveckla ett ramverk för distribuerad styrning för tillstånds-temporalt begränsade system, eftersom flera delsystem är sammankopplade via sina tillståndsbegränsningar som varierar över tiden. Ofta ges sådana begränsningar endast implicit som logiska formler, till exempel i Signal Temporal Logic (STL).  Vår metod för att hantera tillstånds- och tidsmässiga begränsningar är följande. Vi strävar efter att kombinera beräkningseffektiviteten hos återkopplingsregulatorer på låg nivå med planeringsalgoritmer. Återkopplingsregulatorer på låg nivå skall säkerställa att delar av de tillstånds- och tidsmässiga begränsningarna uppfylls, t.ex. sammankopplande tillståndsbegränsningar eller kortsiktiga tidsbegränsningar, medan planeringsalgoritmerna tar hänsyn till de delar som kräver beräkningsintensiva planeringsoperationer. Kraftfulla styrsystem på låg nivå kan förenkla planeringsuppgiften avsevärt. Därför fokuserar vi i denna avhandlingen på utvecklingen av återkopplingsregulatorer på låg nivå.  I den första delen fokuserar vi på att hantera sammankopplande tillståndsbegränsningar för distribuerade system med hjälp av en modell prediktiv styrning (MPC). Vanligtvis kräver den distribuerade hanteringen av kopplingsbegränsningar ett sekventiellt eller iterativt MPC-system som dock är tidskrävande. Därför utvecklar vi en parallelliserad distribuerad modell prediktiv styrning (DMPC) baserad på konsistensbegränsningar. Därigenom garanterar ett delsystem till sina grannar att det håller sig inom ett visst område runt en referensbana. Den generiska formuleringen av vårt DMPC-system möjliggör flera realiseringar. En särskild realisering föreslås. Dessutom utvecklas utvidgningar till ett robust och iterativt system samt ett DMPC-system för system med begränsade dynamiska kopplingar. I den andra delen fokuserar vi på metoder för att säkerställa invariansen av mängder. Vi fokuserar särskilt på kontrollbarriärfunktioner (CBF). Vi visar hur tillstånds- och tidsmässiga begränsningar kan inkodas i icke-glatta tidsvarierande kontrollbarriärfunktioner och hur subgradienter kan användas för att konstruera en effektiv gradientbaserad styrning. För dessa resultat måste antaganden om kontrollerbarhet åberopas. För att utvidga detta resultat till system med svagare kontrollerbarhetsegenskaper undersöker vi kopplingen mellan dynamiska systems kontrollerbarhetsegenskaper och konstruktionen av en CBF. Som ett resultat av detta föreslår vi en konstruktionsmetod för CBF:er som bygger på förutsägelser för ändliga horisonter. Den konstruerade CBF:n uppvisar gynnsamma egenskaper för att utvidga det tidigare resultatet om kodning av rums-temporala begränsningar i CBF:er till system med svagare kontrollerbarhetsegenskaper. Slutligen undersöker vi med hjälp av en fallstudie hur metoder för att säkerställa invariansen av mängder kan användas för att implicit samordna system som är kopplade via tillståndsbegränsningar. Vår föreslagna metod är helt decentraliserad och delsystemen samordnar sig själva endast via sina handlingar och justeringen av sina individuella begränsningar. Slutligen drar vi en slutsats och beskriver hur de presenterade resultaten bidrar till utvecklingen av ett ramverk för distribuerad styrning av tillstånds- och tidsmässigt begränsade system. / <p>QC 20230520</p>

Le thème principal de ce mémoire est la commande sous contraintes pour des systèmes à retard, en tenant compte de la problématique d’échantillonnage (où les informations concernant le système en temps continu sont, par exemple, envoyées par un réseau de communication) et de la présence de contraintes sur les trajectoires du système et sur l’entrée de commande. Pendant le processus d’échantillonnage, le retard variable dans le temps peut être traité comme une incertitude, le but étant de confiner cette variation dans un polytope, de façon à couvrir toutes les variations possibles du retard. Pour stabiliser des systèmes à retard, nous nous sommes basés sur la théorie de Lyapunov. En utilisant cette méthode, nous pouvons trouver un retour d’état qui stabilise le système malgré la présence du retard variable dans la boucle. Une autre possibilité est l’utilisation des candidates de Lyapunov-Krasovskii. La théorie des ensembles invariants est largement utilisée dans ce manuscrit, car il est souhaitable d’obtenir une région de ≪ sûreté ≫, ou le comportement du système est connu, en dépit de la présence du retard (variable) et des contraintes sur les trajectoires du système. Lorsqu’ils sont obtenus dans l’espace d’état augmenté, les ensembles invariants sont très complexes, car la dimension de l’espace Euclidien sera proportionnelle à la taille du système mais aussi à la taille du retard. Le concept de D-invariance est ainsi proposé. La commande prédictive (en anglais MPC) est présentée, pour tenir compte des contraintes sur les trajectoires et appliquer une commande optimale à l’entrée du système. / The main interest of the present thesis is the constrained control of time-delay system, more specifically taking into consideration the discretization problem (due to, for example, a communication network) and the presence of constraints in the system’s trajectories and control inputs. The effects of data-sampling and modeling problem are studied in detail, where an uncertainty is added into the system due to additional effect of the discretization and delay. The delay variation with respect to the sampling instants is characterized by a polytopic supra-approximation of the discretization/delay induced uncertainty. Some stabilizing techniques, based on Lyapunov’s theory, are then derived for the unconstrained case. Lyapunov-Krasovskii candidates were also used to obtain LMI conditions for a state feedback, in the ``original” state-space of the system. For the constrained control purposes, the set invariance theory is used intensively, in order to obtain a region where the system is ``well-behaviored”, despite the presence of constraints and (time-varying) delay. Due to the high complexity of the maximal delayed state admissible set obtained in the augmented state-space approach, in the present manuscript we proposed the concept of set invariance in the ``original” state-space of the system, called D-invariance. Finally, in the las part of the thesis, the MPC scheme is presented, in order to take into account the constraints and the optimality of the control solution.