Model-Based Development and Evaluation of Control for Complex Multi-Domain Systems: Attitude Control for a Quadrotor UAV

A Cyber-Physical System (CPS) incorporates sensing, actuating, computing and communicative capabilities, which are often combined to control the system. The development of CPSs poses a challenge, since the complexity of the physical system dynamics must be taken into account when designing the control application. The physical system dynamics are often defined within mechanical and electrical engineering domains, with the control application residing in software and control engineering domains. Therefore, such a system can be considered multi-domain.With the constant increase in the complexity of such systems, caused by technological advances in all domains, new ways of approaching multi-domain system development are needed. One methodology, which excels in complexity management, is model-based development. Multidomain systems require collaborative modeling, where the physical system dynamics are captured in the Continuous Time (CT) modeling domain and the digital control is captured in the Discrete Event (DE) modeling domain.This thesis demonstrates how an extended CT-first model-based development approach can be applied to a complex multi-domain system. A collaborative model of a quadrotor Unmanned Aerial Vehicle (UAV) has been constructed and used to develop an attitude controller based on Model Predictive Control (MPC). The MPC controller has been compared to an existing open source Proportional Integral Derivative (PID) attitude controller.This thesis contributes to the discipline of model-based development with a methodological extension to the CT-first approach, which extends the conventional approach by expanding the physical modeling process into three consecutive steps. An evaluation of the extension is presented, describing how and when the extended methodology provides increased value

Computer Aided Verification

This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency

Intelligent Control Agent for Autonomous UAS

A self reconfiguring autopilot system is presented, which is based on a rational agent framework that integrates decision making with abstractions of sensing and actions for next generation unmanned aerial vehicles. The objective of the new intelligent control system is to provide advanced capabilities of self-tuning control for a new UAS airframe or adaptation for an old UAS in the presence of failures in adverse flight conditions. High-level system performance is achieved through on-board dynamical monitoring and estimation associated with controller switching and tuning by the agent. The agent can handle an untuned autopilot or retune the autopilot when dynamical changes occur due to aerodynamic and on-board system changes. The system integrates dynamical modelling, hybrid adaptive control, model validation, flight condition diagnosis, control performance evaluation through software agent development. An important feature of the agent is its abstractions from real-time measurements and also its abstractions from model based on-board simulation. The agent, while tuning and supervising the autopilot, also performs real-time evaluations on the effects of its actions

Computer Aided Verification

This open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency

Coordination on Systems of Multiple UAVs

Esta tesis trata acerca de métodos para coordinar las trayectorias de un sistema de Vehículos Aéreos no Tripulados y Autónomos (en adelante UAVs). El primer conjunto de técnicas desarrolladas durante la tesis se agrupan dentro de las técnicas de planificación de trayectorias. En este caso, el objetivo es generar planes de vuelo para un conjunto de vehículos coordinadamente de forma que no se produzcan colisiones entre ellos. Además, este tipo de técnicas puede usarse para modificar el plan de vuelo de un subconjunto de UAVs en tiempo real. Entre los algoritmos desarrollados en la tesis podemos destacar la adaptación de algoritmos evolutivos como los Algoritmos Genéticos y el Particle Swarm (Enjambre de Partículas), la incorporación de nuevas formas de muestreo del espacio para la aplicación del algoritmo Optimal Rapidly Exploring Random Trees (RRT*) en sistemas multi-UAV usando técnicas de muestreo novedosas. También se ha estudiado el comportamiento de parte de estos algoritmos en situaciones variables de incertidumbre del estado del sistema. En particular, se propone el uso del Filtro de Partículas para estimar la posición relativa entre varios UAVs. Además, se estudia la aplicación de métodos reactivos para la resolución de colisiones en tiempo real. Esta tesis propone un nuevo algoritmo para la resolución de colisiones entre múltiples UAVs en presencia de obstáculos fijos llamado G-ORCA. Este algoritmo soluciona varios problemas que han surgido al aplicar el algoritmo ORCA en su variante 3D en sistemas compuestos por vehículos reales. Su seguridad se ha demostrado tanto analíticamente, como empíricamente en pruebas con sistemas reales. De hecho, durante esta tesis numerosos experimentos en sistemas multi-UAV reales compuestos hasta por 4 UAVs han sido ejecutados. En dichos experimentos, se realiza una coordinación autónoma de UAVs en las que se asegura la ejecución de trayectorias libres de colisiones garantizando por tanto la seguridad del sistema. Una característica reseñable de esta tesis es que los algoritmos desarrollados han sido probados e integrados en sistemas más complejos que son usados en aplicaciones reales. En primer lugar, se presenta un sistema para aumentar la duración del vuelo de planeadores aprovechando las corrientes ascendentes de viento generadas por el calor (térmicas). En segundo lugar, un sistema de detección y resolución de colisiones coordinado para sistemas con múltiples UAVs reactivo ha sido diseñado, desarrollado y probado experimentalmente. Este sistema ha sido integrado dentro de un sistema automático de construcción de estructuras mediante múltiples UAVs.The aim of this thesis is to propose methods to coordinately generate trajectories for a system of Autonomous Unmanned Aerial Vehicles (UAVs). The first set of proposed techniques developed in this thesis can be defined as trajectory planning techniques. In this case, the objective is to generate coordinated flight plans for a system of UAVs in such a way that no collision are produced among each pair of UAVs. Besides, these techniques can be applied online in order to modify the original flight plan whenever a potential collision is detected. Amongst the developed algorithms in this thesis we can highlight the adaptation of evolutionary algorithms such as Genetic Algorithms and Particle Swarm, and the application of Optimal Rapidly Exploring Random Trees (RRT*) algorithm into a system of several UAVs with novel sampling techniques. In addition, many of these techniques have been adapted in order to be applicable when only uncertain knowledge of the state of the system is available. In particular, the use of the Particle Filter is proposed in order to estimate the relative position between UAVs. The estimation of the position as well as the uncertainty related to this estimation are then taken into account in the conflict resolution system. All techniques proposed in this thesis have been validated by performing several simulated and real tests. For this purpose, a method for randomly generating a huge test batch is presented in chapter 3. This will allow to test the behavior of the proposed methods in a great variety of situations. During the thesis, several real experimentations with fleets composed by up to four UAVs are presented. In these experiments, the UAVs in the system are automatically coordinated in order to ensure collision-free trajectories and thus guarantee the safety of the system. The other main topic of this thesis is the application of reactive methods for real-time conflict resolution. This thesis proposes a novel algorithm for collision resolution amongst multiple UAVs in the presence of static obstacles, which has been called Generalized-Optimal Reciprocal Collision Avoidance (G-ORCA). This algorithm overcomes several issues that have been detected into the algorithm 3D-ORCA in real applications. A remarkable characteristic of this thesis is that the developed algorithms have been applied as a part of more complex systems. First, a coordinated system for flight endurance extension of gliding aircrafts by profiting the ascending wind is presented. Second, a reactive collision avoidance block has been designed, developed and tested experimentally based in the aforementioned G-ORCA algorithm. This block has been integrated into a system for assembly construction with multiple UAVs

Update urban basemap by using the LiDAR mobile mapping system : the case of Abu Dhabi municipal system

Basemaps are the main resource used in urban planning and in building and infrastructure asset management. These maps are used by citizens and by private and public stakeholders. Therefore, accurate, up-to-date geoinformation of reference are needed to provide a good service. In general, basemaps have been updated by aerial photogrammetry or field surveying, but these methods are not always possible and alternatives need to be sought. Current limitations and challenges that face traditional field surveys include areas with extreme weather, deserts or artic environments, and flight restrictions due to proximity with other countries if there is not an agreement. In such cases, alternatives for large-scale are required. This thesis proposes the use of a mobile mapping system (MMS) to update urban basemaps. Most urban features can be extracted from point cloud using commercial software or open libraries. However, there are some exceptions: manhole covers, or hidden elements even with captures from defferent perspective, the most common building corners. Therefore, the main objective of this study was to establish a methodology for extracting manholes automatically and for completing hidden corners of buildings, so that urban basemaps can be updated. The algorithm developed to extract manholes is based on time, intensity and shape detection parameters, whereas additional information from satellite images is used to complete buildings. Each municipality knows the materials and dimensions of its manholes. Taking advantage of this knowledge, the point cloud is filtered to classify points according to the set of intensity values associated with the manhole material. From the classified points, the minimum bounding rectangles (MBR) are obtained and finally the shape is adjusted and drawn. We use satellite imagery to automatically digitize the layout of building footprints with automated software tools. Then, the visible corners of buildings from the LiDAR point cloud are imported and a fitting process is performed by comparing them with the corners of the building from the satellite image. Two methods are evaluated to establish which is the most suitable for adjustment in these conditions. In the first method, the differences in X and Y directions are measured in the corners, where LiDAR and satellite data are available, and is often computed as the average of the offsets. In the second method, a Helmert 2D transformation is applied. MMS involves Global Navigation Satellite Systems (GNSS) and Inertial Measurement Units (IMU) to georeference point clouds. Their accuracy depends on the acquisition environment. In this study, the influence of the urban pattern is analysed in three zones with varied urban characteristics: different height buildings, open areas, and areas with a low and high level of urbanization. To evaluate the efficiency of the proposed algorithms, three areas were chosen with varying urban patterns in Abu Dhabi. In these areas, 3D urban elements (light poles, street signs, etc) were automatically extracted using commercial software. The proposed algorithms were applied to the manholes and buildings. The completeness and correctness ratio, and geometric accuracy were calculated for all urban elements in the three areas. The best success rates (>70%) were for light poles, street signs and road curbs, regardless of the height of the buildings. The worst rate was obtained for the same features in peri-urban areas, due to high vegetation. In contrast, the best results for trees were found in theses areas. Our methodology demonstrates the great potential and efficiency of mobile LiDAR technology in updating basemaps; a process that is required to achieve standard accuracy in large scale maps. The cost of the entire process and the time required for the proposed methodology was calculated and compared with the traditional method. It was found that mobile LiDAR could be a standard cost-efficient procedure for updating maps.La cartografía de referencia es la principal herramienta en planificación urbanística, y gestión de infraestructuras y edificios, al servicio de ciudadanos, empresas y administración. Por esta razón, debe estar actualizada y ser lo más precisa posible. Tradicionalmente, la cartografía se actualiza mediante fotogrametría aérea o levantamientos terrestres. No obstante, deben buscarse alternativas válidas para escalas grandes, porque no siempre es posible emplear estas técnicas debido a las limitaciones y retos actuales a los que se enfrenta la medición tradicional en algunas zonas del planeta, con meteorología extrema o restricciones de vuelo por la proximidad a la frontera con otros países. Esta tesis propone el uso del sistema Mobile Mapping System (MMS) para actualizar la cartografía urbana de referencia. La mayoría de los elementos pueden extraerse empleando software comercial o librerías abiertas, excepto los registros de servicios. Los elementos ocultos son otro de los inconvenientes encontrados en el proceso de creación o actualización de la cartografía, incluso si se dispone de capturas desde diferentes puntos de vista. El caso más común es el de las esquinas de edificios. Por ello, el principal objetivo de este estudio es establecer una metodología de extracción automática de los registros y completar las esquinas ocultas de los edificios para actualizar cartografía urbana. El algoritmo desarrollado para la detección y extracción de registros se basa en parámetros como el tiempo, la intensidad de la señal laser y la forma de los registros, mientras que para completar los edificios se emplea información adicional de imágenes satélite. Aprovechando el conocimiento del material y dimensión de los registros, en disposición de los gestores municipales, el algoritmo propuesto filtra y clasifica los puntos de acuerdo a los valores de intensidad. De aquellos clasificados como registros se calcula el mínimo rectángulo que los contiene (Minimum Bounding Rectangle) y finalmente se ajusta la forma y se dibuja. Las imágenes de satélite son empleadas para obtener automáticamente la huella de los edificios. Posteriormente, se importan las esquinas visibles de los edificios obtenidas desde la nube de puntos y se realiza el ajuste comparándolas con las obtenidas desde satélite. Para llevar a cabo este ajuste se han evaluado dos métodos, el primero de ellos considera las diferencias entre las coordenadas XY, desplazándose el promedio. En el segundo, se aplica una transformación Helmert2D. MMS emplea sistemas de navegación global por satélite (Global Navigation Satellite Systems, GNSS) e inerciales (Inertial Measurement Unit, IMU) para georreferenciar la nube de puntos. La precisión de estos sistemas de posicionamiento depende del entorno de adquisición. Por ello, en este estudio se han seleccionado tres áreas con distintas características urbanas (altura de edificios, nivel de urbanización y áreas abiertas) de Abu Dhabi con el fin de analizar su influencia, tanto en la captura, como en la extracción de los elementos. En el caso de farolas, señales viales, árboles y aceras se ha realizado con software comercial, y para registros y edificios con los algoritmos propuestos. Las ratios de corrección y completitud, y la precisión geométrica se han calculado en las diferentes áreas urbanas. Los mejores resultados se han conseguido para las farolas, señales y bordillos, independientemente de la altura de los edificios. La peor ratio se obtuvo para los mismos elementos en áreas peri-urbanas, debido a la vegetación. Resultados opuestos se han conseguido en la detección de árboles. El coste económico y en tiempo de la metodología propuesta resulta inferior al de métodos tradicionales. Lo cual demuestra el gran potencial y eficiencia de la tecnología LiDAR móvil para la actualización cartografía de referenciaPostprint (published version

Outdoor operations of multiple quadrotors in windy environment

Coordinated multiple small unmanned aerial vehicles (sUAVs) offer several advantages over a single sUAV platform. These advantages include improved task efficiency, reduced task completion time, improved fault tolerance, and higher task flexibility. However, their deployment in an outdoor environment is challenging due to the presence of wind gusts. The coordinated motion of a multi-sUAV system in the presence of wind disturbances is a challenging problem when considering collision avoidance (safety), scalability, and communication connectivity. Performing wind-agnostic motion planning for sUAVs may produce a sizeable cross-track error if the wind on the planned route leads to actuator saturation. In a multi-sUAV system, each sUAV has to locally counter the wind disturbance while maintaining the safety of the system. Such continuous manipulation of the control effort for multiple sUAVs under uncertain environmental conditions is computationally taxing and can lead to reduced efficiency and safety concerns. Additionally, modern day sUAV systems are susceptible to cyberattacks due to their use of commercial wireless communication infrastructure. This dissertation aims to address these multi-faceted challenges related to the operation of outdoor rotor-based multi-sUAV systems. A comprehensive review of four representative techniques to measure and estimate wind speed and direction using rotor-based sUAVs is discussed. After developing a clear understanding of the role wind gusts play in quadrotor motion, two decentralized motion planners for a multi-quadrotor system are implemented and experimentally evaluated in the presence of wind disturbances. The first planner is rooted in the reinforcement learning (RL) technique of state-action-reward-state-action (SARSA) to provide generalized path plans in the presence of wind disturbances. While this planner provides feasible trajectories for the quadrotors, it does not provide guarantees of collision avoidance. The second planner implements a receding horizon (RH) mixed-integer nonlinear programming (MINLP) model that is integrated with control barrier functions (CBFs) to guarantee collision-free transit of the multiple quadrotors in the presence of wind disturbances. Finally, a novel communication protocol using Ethereum blockchain-based smart contracts is presented to address the challenge of secure wireless communication. The U.S. sUAV market is expected to be worth $92 Billion by 2030. The Association for Unmanned Vehicle Systems International (AUVSI) noted in its seminal economic report that UAVs would be responsible for creating 100,000 jobs by 2025 in the U.S. The rapid proliferation of drone technology in various applications has led to an increasing need for professionals skilled in sUAV piloting, designing, fabricating, repairing, and programming. Engineering educators have recognized this demand for certified sUAV professionals. This dissertation aims to address this growing sUAV-market need by evaluating two active learning-based instructional approaches designed for undergraduate sUAV education. The two approaches leverages the interactive-constructive-active-passive (ICAP) framework of engagement and explores the use of Competition based Learning (CBL) and Project based Learning (PBL). The CBL approach is implemented through a drone building and piloting competition that featured 97 students from undergraduate and graduate programs at NJIT. The competition focused on 1) drone assembly, testing, and validation using commercial off-the-shelf (COTS) parts, 2) simulation of drone flight missions, and 3) manual and semi-autonomous drone piloting were implemented. The effective student learning experience from this competition served as the basis of a new undergraduate course on drone science fundamentals at NJIT. This undergraduate course focused on the three foundational pillars of drone careers: 1) drone programming using Python, 2) designing and fabricating drones using Computer-Aided Design (CAD) and rapid prototyping, and 3) the US Federal Aviation Administration (FAA) Part 107 Commercial small Unmanned Aerial Vehicles (sUAVs) pilot test. Multiple assessment methods are applied to examine the students’ gains in sUAV skills and knowledge and student attitudes towards an active learning-based approach for sUAV education. The use of active learning techniques to address these challenges lead to meaningful student engagement and positive gains in the learning outcomes as indicated by quantitative and qualitative assessments

Naval Aviation Squadron Risk Analysis Predictive Bayesian Network Modeling Using Maintenance Climate Assessment Survey Results

Associated risks in flying have resulted in injury or death to aircrew and passengers, and damage or destruction of the aircraft and its surroundings. Although the Naval Aviation\u27s flight mishap rate declined over the past 60 years, the proportion of human error causal factors has stayed relatively constant at about 80%. Efforts to reduce human errors have focused attention on understanding the aircrew and maintenance actions occurring in complex systems. One such tool has been the Naval Aviation squadrons\u27 regular participation in survey questionnaires deigned to measure respondent ratings related to personal judgments or perceptions of organizational climate for meeting the extent to which a particular squadron achieved the High Reliability Organization (HRO) criteria of achieving safe and reliable operations and maintenance practices while working in hazardous environments. Specifically, the Maintenance Climate Assessment Survey (MCAS) is completed by squadron maintainers to enable leadership to assess their unit\u27s aggregated responses against those from other squadrons. Bayesian Network Modeling and Simulation provides a potential methodology to represent the relationships of MCAS results and mishap occurrences that can be used to derive and calculate probabilities of incurring a future mishap. Model development and simulation analysis was conducted to research a causal relationship through quantitative analysis of conditional probabilities based upon observed evidence of previously occurred mishaps. This application would enable Navy and Marine Corps aviation squadron leadership to identify organizational safety risks, apply focused proactive measures to mitigate related hazards characterized by the MCAS results, and reduce organizational susceptibility to future aircraft mishaps

Simulation of retrospective morphological channel adjustments using high-resolution differential digital elevation models versus predicted sediment delivery and stream power variations

[EN] This work proposes a methodological approach applied to ephemeral gravel-bed streams to verify the change in the magnitude and frequency of hydrological events affecting the morphological dynamics and sediment budget in this type of channel. For the case study, the Azohia Rambla, located in southeastern Spain, was chosen, emphasizing the research on two reference riverbed sections (RCRs): an upper one, with a predominance of erosion, and a middle one, where processes of incision, transport, and deposition were involved. First, this approach focuses on relationships between peak discharges and sediment budgets during the period 2018-2022. For this purpose, water level measurements from pressure sensors, a One-Dimensional Hydrodynamic model, and findings from comparative analyses of high-resolution differential digital elevation models (HRDEM of Difference-HRDoD) based on SfM-MVS and LiDAR datasets were used. In a second phase, the GeoWEPP model was applied to the period 1996-2022 in order to simulate runoff and sediment yield at the event scale for the watersheds draining into both RCRs. During the calibration phase, a sensitivity analysis was carried out to detect the most influential parameters in the model and confirm its capacity to simulate peak flow and sediment delivery in the area described above. Values of NS (Nash-Sutcliffe efficiency) and PBIAS (percent bias) equal to 0.86 and 7.81%, respectively, were found in the calibration period, while these indices were 0.81 and -4.1% in the validation period. Finally, different event class patterns (ECPs) were established for the monitoring period (2018-2022), according to flow stage and morphological channel adjustments (overtopping, bankfull and sub-bankfull, and half-sub-bankfull), and then retrospectively extrapolated to stages of the prior simulated period (1996-2018) from their typical sequences (PECPs). The results revealed a significant increase in the number of events and PECPs leading to lower bed incision rates and higher vertical accretion, which denotes a progressive increase in bed armoring and bank erosion processes.This research was funded by ERDF/Spanish Ministry of Science, Innovation and Universities-State Research Agency (AEI)/Project CGL2017-84625-C2-1-R. State Program for Research, Develop-ment and Innovation focused on the Challenges of SocietyConesa-García, C.; Martínez-Salvador, A.; Puig-Mengual, C.; Martinez-Capel, F.; Pérez-Cutillas, P. (2023). Simulation of retrospective morphological channel adjustments using high-resolution differential digital elevation models versus predicted sediment delivery and stream power variations. Water. 15(15):1-35. https://doi.org/10.3390/w15152697135151