Optimized state feedback regulation of 3DOF helicopter system via extremum seeking

In this paper, an optimized state feedback regulation of a 3 degree of freedom (DOF) helicopter is designed via extremum seeking (ES) technique. Multi-parameter ES is applied to optimize the tracking performance via tuning State Vector Feedback with Integration of the Control Error (SVFBICE). Discrete multivariable version of ES is developed to minimize a cost function that measures the performance of the controller. The cost function is a function of the error between the actual and desired axis positions. The controller parameters are updated online as the optimization takes place. This method significantly decreases the time in obtaining optimal controller parameters. Simulations were conducted for the online optimization under both fixed and varying operating conditions. The results demonstrate the usefulness of using ES for preserving the maximum attainable performance

Autonomous Navigation of Quadrotor Swarms

RÉSUMÉ La mise sur le marché de composants toujours plus performants et compétitifs en termes de coût, ainsi que le développement rapide des technologies de commande et de navigation en robotique, nous ont amenés à envisager le contrôle d’un large essaim de quadrirotors. Di-verses solutions impliquant des drones existent déjà pour différentes applications: inventaire forestier, gestion du littoral, suivi du trafic, etc. Parmi celles-ci, la recherche et le sauvetage en situation d’urgence représentent à nos yeux la possibilité la plus intéressante et constitue, de fait, la première motivation de notre travail. Par conséquent, une large revue de littérature sur la question est fournie. Ce travail se concentre sur le contrôle de l’essaim lui-même, et non sur l’application finale. Tout d’abord, un modèle mathématique de la dynamique du quadrirotor est présenté et plusieurs lois de commande numérique sont synthétisées. Ces dernières implémentent les modes de fonctionnement nécessaires aux algorithmes de navigation, à savoir : commande en vitesse, commande en position et commande en suivi. Ensuite, deux solutions originales et complémentaires de contrôle d’essaim sont proposées. D’une part, un algorithme d’essaimage pour la navigation extérieure est développé. Contrairement à la plupart des travaux trouvés dans la littérature, la solution proposée ici gère non seulement le maintien, mais aussi l’initialisation de la formation. Plus spécifiquement, un modèle de formation hexagonale est introduit. Ensuite, les places en formation sont attribuées de façon optimale à l’aide de l’algorithme hongrois. Enfin, les agents se déplacent jusqu’à la place qui leur est assignée tout en évitant les autres agents avec un algorithme de navigation inspiré du Artificial Potential Field. De plus, cette solution tient compte de contraintes de conception réalistes et a été intégrée avec succès dans un logiciel embarqué de quadrotor déjà existant et opérationnel. Les résultats de simulations Software-In-The-Loop sont fournis. D’autre part, une solution d’essaimage pour la navigation intérieure est étudiée. L’algorithme proposé implémente un certain nombre de comportements individuels simples, de sorte qu’un grand essaim peut suivre un meneur dans des environnements encombrés en se fiant uniquement aux informations locales. Des simulations préliminaires sont effectuées et les résultats montrent qu’il serait possible de faire fonctionner, conformément au besoin étudié, un essaim de cent quadrirotors avec l’algorithme proposé. En particulier, l’essaim est capable de suivre le meneur, de maintenir la connectivité, d’éviter les collisions entre agents, d’éviter les obstacles et même de se faufiler dans des espaces étroits.----------ABSTRACT The ever-growing hardware capabilities and the rapid development of robotic control and navigation technologies have led us to consider the control of an entire swarm of quadrotors. Drone-based solutions have been developed for different applications: forest inventory, coastal management, traÿc monitoring, etc... Among these, the Search And Rescue application represents for us a very promising field of application and constitutes the first motivation of our work. As a result, a wide literature review on the matter is provided. Nevertheless, this work focuses on the swarm control itself, and not on the end user application. First, a mathematical model of the quadrotor dynamics is presented and several digital control laws are designed. The latter provide operating modes useful for the navigation algorithms, namely: velocity control, position control and tracking control. Then, two original and complimentary swarming solutions are proposed. On the one hand, a swarming algorithm for outdoor navigation is developed. Unlike most of the works reviewed in the literature, our solution handles not only the maintenance but also the initialization of the formation. More specifically, an hexagonal formation pattern is intro-duced. Then, positions are optimally assigned using the Hungarian algorithm. Finally, the agents move to their assigned position while avoiding collisions with the other fleet members thanks to a navigation algorithm inspired from Artificial Potential Field. In addition, this solution accounts for realistic design constraints and was successfully integrated into already existing quadrotor onboard software. Software-In-The-Loop simulation results are provided. On the other hand, a swarming solution for indoor navigation is investigated. The proposed algorithm enforces a certain set of expected individual simple behaviors such that a large swarm can follow a leader through cluttered environments relying only on local information. Preliminary simulations are run and the results show that it is possible to operate a swarm of a hundred quadrotors with the proposed algorithm. In particular, the swarm is able to follow the leader, maintain connectivity, avoid collisions with the other agents, avoid obstacles, and even squeeze to pass through narrow spaces

Stochastic Real-time Optimal Control: A Pseudospectral Approach for Bearing-Only Trajectory Optimization

A method is presented to couple and solve the optimal control and the optimal estimation problems simultaneously, allowing systems with bearing-only sensors to maneuver to obtain observability for relative navigation without unnecessarily detracting from a primary mission. A fundamentally new approach to trajectory optimization and the dual control problem is developed, constraining polynomial approximations of the Fisher Information Matrix to provide an information gradient and allow prescription of the level of future estimation certainty required for mission accomplishment. Disturbances, modeling deficiencies, and corrupted measurements are addressed with recursive updating of the target estimate with an Unscented Kalman Filter and the optimal path with Radau pseudospectral collocation methods and sequential quadratic programming. The basic real-time optimal control (RTOC) structure is investigated, specifically addressing limitations of current techniques in this area that lose error integration. The resulting guidance method can be applied to any bearing-only system, such as submarines using passive sonar, anti-radiation missiles, or small UAVs seeking to land on power lines for energy harvesting. Methods and tools required for implementation are developed, including variable calculation timing and tip-tail blending for potential discontinuities. Validation is accomplished with simulation and flight test, autonomously landing a quadrotor helicopter on a wire

Exploiting Heterogeneity in Networks of Aerial and Ground Robotic Agents

By taking advantage of complementary communication technologies, distinct sensing functionalities and varied motion dynamics present in a heterogeneous multi-robotic network, it is possible to accomplish a main mission objective by assigning specialized sub-tasks to specific members of a robotic team. An adequate selection of the team members and an effective coordination are some of the challenges to fully exploit the unique capabilities that these types of systems can offer. Motivated by real world applications, we focus on a multi-robotic network consisting off aerial and ground agents which has the potential to provide critical support to humans in complex settings. For instance, aerial robotic relays are capable of transporting small ground mobile sensors to expand the communication range and the situational awareness of first responders in hazardous environments. In the first part of this dissertation, we extend work on manipulation of cable-suspended loads using aerial robots by solving the problem of lifting the cable-suspended load from the ground before proceeding to transport it. Since the suspended load-quadrotor system experiences switching conditions during this critical maneuver, we define a hybrid system and show that it is differentially-flat. This property facilitates the design of a nonlinear controller which tracks a waypoint-based trajectory associated with the discrete states of the hybrid system. In addition, we address the case of unknown payload mass by combining a least-squares estimation method with the designed controller. Second, we focus on the coordination of a heterogeneous team formed by a group of ground mobile sensors and a flying communication router which is deployed to sense areas of interest in a cluttered environment. Using potential field methods, we propose a controller for the coordinated mobility of the team to guarantee inter-robot and obstacle collision avoidance as well as connectivity maintenance among the ground agents while the main goal of sensing is carried out. For the case of the aerial communications relays, we combine antenna diversity with reinforcement learning to dynamically re-locate these relays so that the received signal strength is maintained above a desired threshold. Motivated by the recent interest of combining radio frequency and optical wireless communications, we envision the implementation of an optical link between micro-scale aerial and ground robots. This type of link requires maintaining a sufficient relative transmitter-receiver position for reliable communications. In the third part of this thesis, we tackle this problem. Based on the link model, we define a connectivity cone where a minimum transmission rate is guaranteed. For example, the aerial robot has to track the ground vehicle to stay inside this cone. The control must be robust to noisy measurements. Thus, we use particle filters to obtain a better estimation of the receiver position and we design a control algorithm for the flying robot to enhance the transmission rate. Also, we consider the problem of pairing a ground sensor with an aerial vehicle, both equipped with a hybrid radio-frequency/optical wireless communication system. A challenge is positioning the flying robot within optical range when the sensor location is unknown. Thus, we take advantage of the hybrid communication scheme by developing a control strategy that uses the radio signal to guide the aerial platform to the ground sensor. Once the optical-based signal strength has achieved a certain threshold, the robot hovers within optical range. Finally, we investigate the problem of building an alliance of agents with different skills in order to satisfy the requirements imposed by a given task. We find this alliance, known also as a coalition, by using a bipartite graph in which edges represent the relation between agent capabilities and required resources for task execution. Using this graph, we build a coalition whose total capability resources can satisfy the task resource requirements. Also, we study the heterogeneity of the formed coalition to analyze how it is affected for instance by the amount of capability resources present in the agents

Automatic Flight Control Systems

The history of flight control is inseparably linked to the history of aviation itself. Since the early days, the concept of automatic flight control systems has evolved from mechanical control systems to highly advanced automatic fly-by-wire flight control systems which can be found nowadays in military jets and civil airliners. Even today, many research efforts are made for the further development of these flight control systems in various aspects. Recent new developments in this field focus on a wealth of different aspects. This book focuses on a selection of key research areas, such as inertial navigation, control of unmanned aircraft and helicopters, trajectory control of an unmanned space re-entry vehicle, aeroservoelastic control, adaptive flight control, and fault tolerant flight control. This book consists of two major sections. The first section focuses on a literature review and some recent theoretical developments in flight control systems. The second section discusses some concepts of adaptive and fault-tolerant flight control systems. Each technique discussed in this book is illustrated by a relevant example

Aerial Vehicles

This book contains 35 chapters written by experts in developing techniques for making aerial vehicles more intelligent, more reliable, more flexible in use, and safer in operation.It will also serve as an inspiration for further improvement of the design and application of aeral vehicles. The advanced techniques and research described here may also be applicable to other high-tech areas such as robotics, avionics, vetronics, and space

UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

Reliable and Safe Motion Control of Unmanned Vehicles

Unmanned vehicles (UVs) are playing an increasingly significant role in modern daily life. In the past decades, numerous commercial, scientific, and military communities across the world are developing fully autonomous UVs for a variety of applications, such as environmental monitoring and surveillance, post-disaster search and rescue, border patrol, natural resources exploration, and experimental platforms for new technologies verification. The excessive opportunities and threats that come along with these diverse applications have created a niche demand for UVs to extend their capabilities to perform more sophisticated and hazardous missions with greater autonomy, lower costs of development and operation, improved personnel safety and security, extended operational range (reliability) and precision, as well as increased flexibility in sophisticated environments including so-called dirty, dull, harsh, and dangerous missions. In order to successfully and effectively execute missions and meet their corresponding performance criteria and overcome these ever-increasing challenges, greater autonomy together with more advanced reliable and safe motion control systems are required to offer the critical technologies for ensuring intelligent, safe, reliable, and efficient control of UVs in the presence of disturbances, actuator saturation, and even actuator faults, especially for practical applications. This thesis concentrates on the development of different reliable and safe motion control algorithms/strategies applicable to UVs, in particular, unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). A number of contributions pertaining to the fault detection and diagnosis (FDD), fault-tolerant control (FTC), disturbance estimation and compensation, and actuator saturation avoidance have been made in this thesis. In addition to the control problems, this thesis also presents several guidance-related contributions, including adaptive observer-based line-of-sight (LOS) guidance law, time-varying lookahead distance scheme, piecewise path switching criterion for guiding a single UV, as well as a proportional-integral (PI) type of leader-follower formation guidance strategy for a group of UVs