Nonlinear predictive control of autonomous soaring UAVs using 3DOF models

We design a nonlinear model predictive control (NMPC) system for a soaring UAV in order to harvest the energy from the atmospheric updrafts. Our control framework combines an online estimation with a heuristic search method to obtain the UAV optimal trajectory. To allow for real-time computation of the control commands we solve the optimal control problem using a 3 degrees-of-freedom (DOF) model but apply the inputs to a more realistic 6DOF model. Hence, we design a 3DOF-6DOF model interaction strategy. Simulations show how the control system succeeds in energy extraction in a challenging dynamic atmospheric environment while satisfying its real-time contraints

Onboard Robust Nonlinear Control for Multiple Multirotor UAVs

In this thesis, we focus on developing and validating onboard robust nonlinear control approaches for multiple multirotor unmanned aerial vehicles (UAVs), for the promise of achieving nontrivial tasks, such as path following with aggressive maneuvers, navigation in complex environments with obstacles, and formation in group. To fulfill these challenging missions, the first concern comes with the stability of flight control for the aggressive UAV maneuvers with large tilted angles. In addition, robustness of control is highly desired in order to lead the multirotor UAVs to safe and accurate performance under disturbances. Furthermore, efficiency of control algorithm is a crucial element for the onboard implementation with limited computational capability. Finally, the potential to simultaneously control a group of UAVs in a stable fashion is required. All of these concerns motivate our work in this thesis in the following aspects. We first propose the problem of robust control for the nontrivial maneuvers of a multirotor UAV under disturbances. A complete framework is developed to enable the UAV to achieve the challenging tasks, which consists of a nonlinear attitude controller based on the solution of global output regulation problems for the rigid body rotations SO(3), a backstepping-like position controller, a six-dimensional (6D) wrench observer to estimate the unknown force and torque disturbances, and an online trajectory planner based on a model predictive control (MPC) method. We prove the strong convergence properties of the proposed method both in theory and via intensive real-robot experiments of aggressive waypoint navigation and large-tilted path following tasks in the presence of external disturbances, e.g. wind gusts. Secondly, we propose the problem of autonomous navigation of a multirotor UAV in complex scenarios. We present an effective and robust control approach, namely a fast MPC method with the inclusion of nonlinear obstacle avoiding constraints, and implement it onboard the UAV at 50Hz. The developed approach enables the navigation for a multirotor UAV in 3D environments with multiple obstacles, by autonomously deciding to fly over or around the randomly located obstacles. The third problem that is addressed in our work is formation control for a group of multirotor UAVs. We solve this problem by proposing a distributed formation control algorithm for multiple UAVs based on the solution of retraction balancing problem. The algorithm brings the whole group of UAVs simultaneously to a prescribed submanifold that determines the formation shape in an asymptotically stable fashion in 2D and 3D environments. We validate our proposed algorithm via a series of hardware-in-the-loop simulations and real-robot experiments in various formation cases of arbitrary time-varying (e.g. expanding, shrinking or moving) shapes. In the actual experiments, up to 4 multirotors have been implemented to form arbitrary triangular, rectangular and circular shapes drawn by the operator via a human-robot-interaction device. We have also carried out virtual tests using up to 6 onboard computers to achieve a spherical formation and a formation moving through obstacles.In dieser Arbeit konzentrieren wir uns auf die Entwicklung und Validierung von robusten nichtlinearen On-Bord Steuerungsansatzen für mehrere unbemannte Multirotor-Luftfahrzeuge (UAVs), mit dem Ziel, nicht triviale Aufgaben zu erledigen wie z.B. Wegfolge mit aggressiven Manovern, Navigation in komplexen Umgebungen mit Hindernissen und Formationsflug in einer Gruppe. Um diese anspruchsvollen Missionen zu erfullen liegt unser Hauptaugenmerk bei der Stabilität der Flugsteuerung für aggressive UAV Manöver mit steilen Lagewinkeln. Des weiteren ist Kontroll-robustheit sehr wünschenswert, um die Multirotor-UAVs unter Beeinflussung sicher und genau zu steuern. Daruber hinaus ist die Effizienz des Kontrollalgorithmus ein wichtiges Element für die Onboard-Implementierung mit eingeschrankter Rechenfähigkeit. Abschliessend ist das Potenzial, gleichzeitig eine Gruppe von UAVs in stabiler Weise zu kontrollieren, erforderlich. All dies motiviert uns zur Arbeit an den folgenden Aspekten: Zuerst behandeln wir das Problem der robusten Steuerung nichttrivialer Manöver eines Multirotor UAV unter Störeinfluss. Ein komplettes Framework wird entwickelt, welches dem UAV ermöglicht diese anspruchsvollen Aufgaben zu bewältigen. Es beinhaltet einem nichtlinearen Lageregler, basierend auf der Lösung von globalen Ausgangsrege lungsproblemen für Starrkörperrotationen SO(3), einem backstepping basierten Positionsregler, einen sechsdimensionalen (6D) wrench observer um die unbekannten Kraftund Drehmomenteinflusse zu schätzen, sowie einem Online-Trajektorienplaner basierend auf Model Predictive Control (MPC). Wir weisen die starken Konvergenzcharakteristiken der vorgeschlagenen Methode nach, sowohl in der Theorie als auchmittels intensiver Real-roboter-Experimente, mit aggressiver Wegpunktnavigation und Wegfindungsaufgaben in extremer Fluglage in Gegenwart externer Einflüsse, z.B. Windböen. Als nächstes bearbeiten wir das Problem der autonomen Navigation eines Multirotor UAV in komplexen Szenarien. Wir stellen einen effektiven und robusten Steuerungsansatz dar, nämlich eine schnelle MPC-Methode mit der Einbeziehung von nichtlinearer Einschränkungen zur Hindernisvermeidung, und implmenetieren diese an Bord des UAV mit 50Hz. Der entwickelte Ansatz ermöglicht die Navigation eines Multirotor UAVs in 3D-Umgebungen mit mehreren Hindernissen, wobei autonom entschieden wir, über oder um die zufällig gelegenen Hindernisse zu fliegen. Das dritte Problem, das in unserer Arbeit angesprochen wird, ist die Bildungssteuerung für eine Gruppe von Multirotor UAVs. Wir lösen dieses Problem, indem wir einen verteilten Formationskontrollalgorithmus für mehrere UAVs auf der Grundlage der Lösung des Retraction Balancing Problems vorschlagen. Der Algorithmus bringt die ganze Gruppe von UAVs gleichzeitig auf eine vorgeschriebene Untermanigfaltigkeit, welche die Formation in asymtotisch stabiler Weise in 2D- und 3D-Umgebungen bestimmt. Wir validieren unseren vorgeschlagenen Algorithmus uber eine Reihe von Hardware-in-the- ¨ Loop-Simulationen und Real-Roboter-Experimente mit verschiedenen Formationsvarianten in beliebigen zeitveränderlichen (z. B. expandierenden, schrumpfenden oder bewegten) Formen. In den eigentlichen Experimenten wurden bis zu 4 Multirotoren eingesetzt, um beliebige dreieckige, rechteckige und kreisförmige Formen zu bilden, die vom Bediener über eine Mensch-Roboter-Interaktionsvorrichtung vorgezeichnet wurden. Wir haben auch virtuelle Tests mit bis zu 6 Onboard-Computern durchgeführt, um eine sphärische Formation und eine Formation zu erreichen, die sich durch Hindernisse. bewegt

Impatient Online Matching

We investigate the problem of Min-cost Perfect Matching with Delays (MPMD) in which requests are pairwise matched in an online fashion with the objective to minimize the sum of space cost and time cost. Though linear-MPMD (i.e., time cost is linear in delay) has been thoroughly studied in the literature, it does not well model impatient requests that are common in practice. Thus, we propose convex-MPMD where time cost functions are convex, capturing the situation where time cost increases faster and faster. Since the existing algorithms for linear-MPMD are not competitive any more, we devise a new deterministic algorithm for convex-MPMD problems. For a large class of convex time cost functions, our algorithm achieves a competitive ratio of O(k) on any k-point uniform metric space. Moreover, our deterministic algorithm is asymptotically optimal, which uncover a substantial difference between convex-MPMD and linear-MPMD which allows a deterministic algorithm with constant competitive ratio on any uniform metric space

A proposed EPRI tailored collaboration project

After five years of extensive R&D sponsored by government and industry, the coal log pipeline (CLP) technology for transportation of coal has been sufficiently developed through laboratory tests to warrant large-scale pre-commercial demonstration and testing. Meanwhile, a national survey of electric utilities and coal companies has produced fourteen potential CLP demonstration sites. A preliminary evaluation of the sites determined that at least seven of the fourteen sites are economically promising. The purpose of this EPRI-TC proposal is to conduct a large-scale pre-commercial test/demo of CLP to pave the way for commercial demonstration. Completion of this pre-commercial test/demo project in two years will enable construction of the first commercial CLP with minimum risk involved and with maximum success. The CLP technology involves compaction of coal into logs (large circular coal cylinders), and the transportation of such logs by an underground pipeline to the user--a power generation station. It is an innovative new coal pipeline system that can effectively compete with railroads and truck transportation. The economics of CLP has been thoroughly examined in 1995. It was found that the CLP is economically competitive with train for distances greater than about 100 miles, and competitive with truck for distances greater than about 30 miles. As compared to coal slurry pipeline, the CLP has the following advantages: (1) CLP transports twice as much coal than a coal slurry pipeline of the same diameter can. The cost of coal transportation by CLP is substantially lower than by slurry pipeline. (2) Dewatering coal logs is much simpler than dewatering slurry. (3) CLP can be restarted readily after lengthy shutdown. It has no restart problem. (4) CLP uses less energy than slurry pipeline for transporting the same amount of coal. (5) Coal log fuel is most versatile. Upon crushing it can be burned in any type of combustors--pulverized-coal, cyclone, fluidized-bed, or stoker. (6) Storage of coal logs is much simpler than storage of coal slurry. (7) CLP uses only 1/3 to 1/4 of the water used by slurry pipeline. This makes CLP more feasible than slurry pipeline in regions of water shortage. Development of the CLP technology will benefit electric utilities by reducing coal transportation cost--not only through use of CLP, but also due to the competition fostered which will cause rail rates and truck rates to keep within bounds. The pre-commercial test/demo project proposed herein contains four major components or tasks: (1) construction of a 6-inch-diameter, 3,000-ft-long coal pipeline for testing coal logs under conditions similar to those of future commercial CLP; (2) construction and testing of a coal log machine that can rapidly manufacture coal logs to supply coal log pipelines; (3) conducting a site-specific application study for each participating utilities; and (4) conducting an economic analysis of future commercial CLP systems using information gained in this study, and following EPRI cost guidelines. The project is for two years at a total cost of $825,960 of which$500,000 is requested from EPRI and participating utilities. As an EPRI Tailored Collaboration project, each participating utility is asked to contribute a total of $60,000 over two years (with equal matching from EPRI) to support this project. The targeted amount from utilities and EPRI for this project is$600,000 of which $100,000 is indirect cost to be used by EPRI to administer this project. This targeted amount can be achieved with five electric utilities participating. The project will also be cost-shared with$325,960 of the existing funds of the Capsule Pipeline Research Center (CPRC). Currently, the CPRC has insufficient funds to carry out this project without support from EPRI and some additional utility companies.Introduction -- Advantages of CLP -- Brief review of concept and state of development -- Project purpose and tasks -- Test facilities -- Statement of work -- Schedule of activities -- References -- Qualifications of institute and project personnel -- Budget -- Budget explanation -- Utilities participation and arrangements -- Intellectual property rights and patents -- Appendices. Document on preparing smooth welded joints for steel pipe ; CPRC's contract document (agreement) with existing industrial sponsors