Unmanned Aerial Vehicles (UAV) control has become a very important point of scientific study. The control design challenges of a UAV make it one of the most researched areas in modern control applications. This thesis specifically chooses the Quadrotor as the UAV platform. Considering the quadrotor has 4 rotors and 6 degrees of freedom, it is an underactuated system and is dynamically unstable that has to be stabilized by a suitable control algorithm in order to operate autonomously. This thesis focuses on the quaternion representation of the quadrotor system dynamics and develops an adaptive control for its trajectory tracking problem. The control design uses the certainty equivalence principle where adaptive tracking controls are designed separately for each of the translational and rotational subsystems. With this approach, the success of the outer loop translational control relies on the fast convergence of the inner loop rotational control in order to guarantee the system’s stability while achieving the tracking objective. For the translational subsystem in the outer loop, a modified geometric control technique is considered with an adaptive component for the estimation of the uncertain mass of the quadrotor. For the rotational subsystem in the inner loop a backstepping based control design is adopted due to its systematic design and intuitive approach. An adaptive component is further integrated with it to estimate the integrated components of the uncertain Moment of Inertia matrix and other constant parameters in the system dynamics to guarantee the stability of the inner loop system while achieving the tracking objective. Furthermore, a complete backstepping control design methodology is presented which overcomes the issues of certainty equivalence principle where the inner loop needs to execute significantly faster than the outer loop to stabilize the system.

The use of small scale Unmanned Aerial Vehicles (UAVs) is quickly becomingcommonplace in many domains. Operating such vehicles often requires using aspecialized radio control (RC) transmitter. One objective of this thesis is toinvestigate the use of other means of controlling a particular type of a UAV - aquadrotor. Two types of alternative devices are investigated, a standard gamingconsole controller PlayStation 3 gamepad (PS3 gamepad) and a smartphone(Android OS based). The purpose of substituting the RC controller is to make iteasier for a novice user to operate a UAV. The second objective is to investigate solutions to the problem of slung load control. A slung load is a uniform mass attached to a platform with a wire that may swingfreely. The slung load control problem consists of several subproblems: slung loadmodeling, altitude control, filtering of sensor data and the slung load control itself. The purpose of controlling the slung load is to reduce the oscillations of the load inflight and to minimize its influence on the flight performance of a UAV. Both types of alternative interfaces to the UAV were designed and implemented. Inorder to interface with the quadrotor platform at hand a new communicationprotocol based on TCP/IP was introduced. A study of the design process and typicaluse cases was performed. The two types of interfaces were evaluated by a group oftarget users as well as in real flight tests. The game controller was easy to use whilethe smartphone interface required automatic altitude control to be really useful. The evaluators found that the smartphone provided a smoother control over the steeringcompared to using the joystick on a game controller. The slung load control problem was investigated theoretically and in practice on astationary testing rig. The altitude control problem has been addressed byincorporating a PID controller which uses filtered data from a pressure sensor. ThePID control was extended with an anti-windup mechanism combined with afeedforward control of the tilt angle. A mechanism for a smooth transition from themanual to automatic altitude control modes was implemented and verified in flighttests.

Quadrotors are a type of aircraft that lately has gained increased popularity within the UAV-scientific area. Many research groups around the world have implemented control systems that allow for autonomous flight of quadrotors with the help of the known dynamics. This thesis presents two approaches to modelling the dynamics of the quadrotor. The first is a linear greybox approach where the structure is derived from known equations and some constants are measured and some identified through system identification techniques. The second model is a blackbox model where a neural network is trained and used. The two models are then evaluated using known error measurements with the help of previously recorded flight data and the results are presented. It is for example shown that with the untreated flight data the traditional greybox model have accurate dynamics but is sensitive to noise and drifts in the measurements. It is also shown that better results generally can be achieved using a neural network model, especially for noisy unpreprocessed data.

Cooperative control of multi-agent systems (MASs) has been intensively investigated in the past decade. The task is always complicated for an individual agent, but can be achieved by collectively operating a group of agents in a reliable, economic and efficient way. Although a lot of efforts are being spent on improving MAS performances, much progress has yet to be developed on different aspects. This thesis aims to solve problems in the consensus control of multiple quadrotors and/or mobile robots considering irregular sampling controls, heterogeneous agent dynamics and the presence of model uncertainties and disturbances. The thesis proceeds with Chapter 1 by providing the literature review of the state-of-the-art development in the consensus control of MASs. Chapter 2 introduces experimental setups of the laboratory involving two-wheeled mobile robots (2WMRs), quadrotors, positioning systems and inter-vehicle communications. All of the developed theoretical results in Chapters 3-6 are experimentally verified on the platform. Then it is followed by two main parts: Irregular sampling consensus control methods (Chapter 3 and 4) and cooperative control of heterogeneous MASs (Chapter 5 and 6). Chapter 3 focuses on the non-uniform sampling consensus control for a group of 2WMRs, and Chapter 4 studies the event-based rendezvous control for a group of asynchronous robots with time-varying communication delays. Chapter 5 concentrates on cooperative control methods for a heterogeneous MAS consisting of quadrotors and 2WMRs. Chapter 6 focuses on the design of a quadrotor flight controller which is robust to various adverse factors such as model uncertainties and external disturbances. The developed controller is further applied to the consensus control of the heterogeneous MAS. Specifically, Chapter 3 studies synchronized and non-periodical sampling consensus control methods for a group of 2WMRs. The directed and switching communication topologies among the network are considered in the controller design. The 2WMR is an underactuated system, which implies that it can not generate independent x and y accelerations in the two-dimensional plane. The rendezvous control methods are proposed for 2WMRs. The algebraic graph theory and stochastic matrix analysis are employed to conduct the convergence analysis. Although the samplings in the work of Chapter 3 are aperiodic, one feature is that local clocks of agents are required to be synchronized. Challenges arise in the practical control of distributed MASs, especially in the scenario that the global clock is lacking. Moreover, frequent samplings can result in redundant information transmissions when the communication bandwidth is limited. To address these problems, Chapter 4 investigates an event-based rendezvous control method for a group of asynchronous MAS with time-varying communication delays. Integral-type triggering conditions for each robot are adopted to be checked periodically. If the triggering condition is satisfied at one checking instant, the agent samples and broadcasts the state to the neighbors with a bounded communication delay. Then an algorithm is provided for driving 2WMRs to asymptotically reach rendezvous. The convergence analysis is conducted through Lyapunov approaches. Most of the theoretical works on cooperative control are focused on controlling agents with identical dynamics. However, in certain realistic scenarios, some complex missions require the cooperation of different types of agent dynamics such as surveillance, search and rescue, etc. Tasks can be carried out with higher efficiency by employing both the autonomous ground vehicles and unmanned aerial vehicles. To achieve better performance for MASs, in Chapter 5, distributed cooperative control methods for a heterogeneous MAS consisting of quadrotors and 2WMRs are developed. Consensus conditions are provided, and the theoretical results are experimentally verified. Many existing quadrotor control methods need exact model parameters of the quadrotor. In reality, when a quadrotor is conducting some tasks with extra payloads or with unexpected damages to the model structure, errors in parameters could result in the failure of the flight. External disturbances also inevitably affect the flight performance. To move a step further towards practical applications, in Chapter 6, a robust quadrotor flight controller using Integral Sliding Mode Control (ISMC) technique is investigated. In experiments, an extra payload with the position and mass unknown, is attached to destroy the accuracy of the model and to add disturbances. The designed controller significantly rejects negative effects caused by the payload during the flight. This controller is also successfully applied to an MAS consisting of a quadrotor and 2WMRs. / Graduate

During this master thesis an adaptive control system for angular velocity was developed. The approach focuses on radio controlled quadrotors and thereby targets a computational efficient solution. The adaptation is divided into two steps. First, an Integral Squared Plus Time Delay (I2PD) model estimation is done through the Recursive Least Squares (RLS) algorithm. Second, control parameters for the quadrotors Proportional Integral Derivative (PID) controller are found by using empirically modified Tuning Rules (TRs) which are based on the I2PD model. Simulation results show the benefits of an adaptive tuning algorithm in regards of the time consuming process of manually tuning a PID controller as well as robustness against both predictable and unpredictable system changes. This includes actuator degradation, battery consumption, changes in weight or inertia etc. However, it is apparent that the tuning algorithm demands an arbitrary initial approximation to be stable at initialization.

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.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23504号 / 工博第4916号 / 新制||工||1768(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 松野 文俊, 教授 泉田 啓, 教授 藤本 健治 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

Quadrotors, being more agile than fixed-wing vehicles, are the ideal candidates for autonomous missions in small, compact spaces. The immense challenge to navigate such environments is fulfilled by the concept of path following. Path following is the method of tracking/tracing a fixed, pre-defined path with minimum position error while exerting the lowest possible control effort. In this work, the missile guidance technique of pure pursuit is adopted and modified for a 3D quadrotor model to follow fixed, compact trajectories. A specialized hardware testing platform is developed to test this algorithm. The results obtained from simulation and flight tests are compared to results from another technique called differential flatness. A small part of this thesis also deals with the stability analysis of the modified 3D pure pursuit algorithm to track trajectories expending lower control effort.

La planification de mouvement est le domaine de l’informatique qui a trait au développement de techniques algorithmiques permettant la génération automatique de trajectoires pour un système mécanique. La nature d’un tel système varie selon les champs d’application. En animation par ordinateur il peut s’agir d’un avatar humanoïde. En biologie moléculaire cela peut être une protéine. Le domaine d’application de ces travaux étant la robotique aérienne, le système est ici un UAV (Unmanned Aerial Vehicle: véhicule aérien sans pilote) à quatre hélices appelé quadrirotor. Le problème de planification de mouvements consiste à calculer une série de mouvements qui amène le système d’une configuration initiale donnée à une configuration finale souhaitée sans générer de collisions avec son environnement, la plupart du temps connu à l’avance. Les méthodes habituelles explorent l’espace des configurations du système sans tenir compte de sa dynamique. Cependant, la force de poussée qui permet à un quadrirotor de voler est par construction parallèle aux axes de rotation des hélices, ce qui implique que certains mouvements ne peuvent pas être effectués. De plus, l’intensité de cette force de poussée, et donc l’accélération linéaire du centre de masse, sont limitées par les capacités physiques du robot. Pour toutes ces raisons, non seulement la position et l’orientation doivent être planifiées, mais les dérivées plus élevées doivent l’être également si l’on veut que le système physique soit en mesure de réellement exécuter le mouvement. Lorsque c’est le cas, on parle de planification kinodynamique de mouvements. Une distinction est faite entre le planificateur local et le planificateur global. Le premier est chargé de produire une trajectoire valide entre deux états du système sans nécessairement tenir compte des collisions. Le second est l’algorithme principal qui est chargé de résoudre le problème de planification de mouvement en explorant l’espace d’état du système. Il fait appel au planificateur local. Nous présentons un planificateur local qui interpole deux états comprenant un nombre arbitraire de degrés de liberté ainsi que leurs dérivées premières et secondes. Compte tenu d’un ensemble de limites sur les dérivées des degrés de liberté jusqu’au quatrième ordre (snap), il produit rapidement une trajectoire en temps minimal quasi optimale qui respecte ces limites. Dans la plupart des algorithmes modernes de planification de mouvements, l’exploration est guidée par une fonction de distance (ou métrique). Le meilleur choix pour celle-ci est le cost-to-go, c.a.d. le coût associé à la méthode locale. Dans le contexte de la planification kinodynamique de mouvements, il correspond à la durée de la trajectoire en temps minimal. Le problème dans ce cas est que calculer le cost-to-go est aussi difficile (et donc aussi coûteux) que de calculer la trajectoire optimale elle-même. Nous présentons une métrique qui est une bonne approximation du cost-to-go, mais dont le calcul est beaucoup moins coûteux. Le paradigme dominant en planification de mouvements aujourd’hui est l’échantillonnage aléatoire. Cette classe d’algorithmes repose sur un échantillonnage aléatoire de l’espace d’état afin de l’explorer rapidement. Une stratégie commune est l’échantillonnage uniforme. Il semble toutefois que, dans notre contexte, ce soit un choix assez médiocre. En effet, une grande majorité des états uniformément échantillonnés ne peuvent pas être interpolés. Nous présentons une stratégie d’échantillonnage incrémentale qui diminue considérablement la probabilité que cela ne se produise. / Motion planning is the field of computer science that aims at developing algorithmic techniques allowing the automatic computation of trajecto- ries for a mechanical system. The nature of such a system vary according to the fields of application. In computer animation it could be a humanoid avatar. In molecular biology it could be a protein. The field of application of this work being aerial robotics, the system is here a four-rotor UAV (Unmanned Aerial Vehicle) called quadrotor. The motion planning problem consists in computing a series of motions that brings the system from a given initial configuration to a desired final configuration without generating collisions with its environment, most of the time known in advance. Usual methods explore the system’s configuration space regardless of its dynamics. By construction the thrust force that allows a quadrotor to fly is tangential to its attitude which implies that not every motion can be performed. Furthermore, the magnitude of this thrust force and hence the linear acceleration of the center of mass are limited by the physical capabilities of the robot. For all these reasons, not only position and orientation must be planned, higher derivatives must be planned also if the motion is to be executed. When this is the case we talk of kinodynamic motion planning. A distinction is made between the local planner and the global planner. The former is in charge of producing a valid trajectory between two states of the system without necessarily taking collisions into account. The later is the overall algorithmic process that is in charge of solving the motion planning problem by exploring the state space of the system. It relies on multiple calls to the local planner. We present a local planner that interpolates two states consisting of an arbitrary number of degrees of freedom (dof) and their first and second derivatives. Given a set of bounds on the dof derivatives up to the fourth order (snap), it quickly produces a near-optimal minimum time trajectory that respects those bounds. In most of modern global motion planning algorithms, the exploration is guided by a distance function (or metric). The best choice is the cost-to-go, i.e. the cost associated to the local method. In the context of kinodynamic motion planning, it is the duration of the minimal-time trajectory. The problem in this case is that computing the cost-to-go is as hard (and thus as costly) as computing the optimal trajectory itself. We present a metric that is a good approximation of the cost-to-go but which computation is far less time consuming. The dominant paradigm nowadays is sampling-based motion planning. This class of algorithms relies on random sampling of the state space in order to quickly explore it. A common strategy is uniform sampling. It however appears that, in our context, it is a rather poor choice. Indeed, a great majority of uniformly sampled states cannot be interpolated. We present an incremental sampling strategy that significantly decreases the probability of this happening.

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