Model-Based Control Using Model and Mechanization Fusion Techniques for Image-Aided Navigation

Unmanned aerial vehicles are no longer used for just reconnaissance. Current requirements call for smaller autonomous vehicles that replace the human in high-risk activities. Many times these activities are performed in GPS-degraded environments. Without GPS providing today\u27s most accurate navigation solution, autonomous navigation in tight areas is more difficult. Today, image-aided navigation is used and other methods are explored to more accurately navigate in such areas (e.g., indoors). This thesis explores the use of inertial measurements and navigation solution updates using cameras with a model-based Linear Quadratic Gaussian controller. To demonstrate the methods behind this research, the controller will provide inputs to a micro-sized helicopter that allows the vehicle to maintain hover. A new method for obtaining a more accurate navigation solution was devised, originating from the following basic setup. To begin, a nonlinear system model was identified for a micro-sized, commercial, off-the-shelf helicopter. This model was verified, then linearized about the hover condition to construct a Linear Quadratic Regulator (LQR). The state error estimates, provided by an Unscented Kalman Filter using simulated image measurement updates, are used to update the navigation solution provided by inertial measurement sensors using strapdown mechanization equations. The navigation solution is used with a reference signal to determine the position and heading error. This error, along with other states, is fed to the LQR, which controls the helicopter. Research revealed that by combining the navigation solution from the INS mechanization block with a model-based navigation solution, and combining the INS error model and system model during the time propagation in the UKF, the navigation solution error decreases by 20%. The equations used for this modification stem from state and covariance combination methods utilized in the Federated Kalman Filter

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Modeling, Simulation, and Flight Test for Automatic Flight Control of the Condor Hybrid-Electric Remote Piloted Aircraft

This thesis describes the modeling and verification process for the stability and control analysis of the Condor hybrid-electric Remote-Piloted Aircraft (HE-RPA). Due to the high-aspect ratio, sailplane-like geometry of the aircraft, both longitudinal and lateral/directional aerodynamic moments and effects are investigated. The aircraft is modeled using both digital DATCOM as well as the JET5 Excel-based design tool. Static model data is used to create a detailed assessment of predictive flight characteristics and PID autopilot gains that are verified with autonomous flight test. PID gain values were determined using a six degree of freedom linear simulation with the Matlab/SIMULINK software. Flight testing revealed an over-prediction of the short period poles natural frequency, and a prediction to within 0.5% error of the long-period pole frequency. Flight test results show the tuned model PID gains produced a 21.7% and 44.1% reduction in the altitude and roll angle error, respectively. This research effort was successful in providing an analytic and simulation model for the hybrid-electric RPA, supporting first-ever flight test of parallel hybrid-electric propulsion system on a small RPA

Fault-detection on an experimental aircraft fuel rig using a Kalman filter-based FDI screen

Reliability is an important issue across industry. This is due to a number of drivers such as the requirement of high safety levels within industries such as aviation, the need for mission success with military equipment, or to avoid monetary losses (due to unplanned outage) within the process and many other industries. The application of fault detection and identification helps to identify the presence of faults to improve mission success or increase up-time of plant equipment. Implementation of such systems can take the form of pattern recognition, statistical and geometric classifiers, soft computing methods or complex model based methods. This study deals with the latter, and focuses on a specific type of model, the Kalman filter. The Kalman filter is an observer which estimates the states of a system, i.e. the physical variables, based upon its current state and knowledge of its inputs. This relies upon the creation of a mathematical model of the system in order to predict the outputs of the system at any given time. Feedback from the plant corrects minor deviation between the system and the Kalman filter model. Comparison between this prediction of outputs and the real output provides the indication of the presence of a fault. On systems with several inputs and outputs banks of these filters can used in order to detect and isolate the various faults that occur in the process and its sensors and actuators. The thesis examines the application of the diagnostic techniques to a laboratory scale aircraft fuel system test-rig. The first stage of the research project required the development of a mathematical model of the fuel rig. Test data acquired by experiment is used to validate the system model against the fuel rig. This nonlinear model is then simplified to create several linear state space models of the fuel rig. These linear models are then used to develop the Kalman filter Fault Detection and Identification (FDI) system by application of appropriate tuning of the Kalman filter gains and careful choice of residual thresholds to determine fault condition boundaries and logic to identify the location of the fault. Additional performance enhancements are also achieved by implementation of statistical evaluation of the residual signal produced and by automatic threshold calculation. The results demonstrate the positive capture of a fault condition and identification of its location in an aircraft fuel system test-rig. The types of fault captured are hard faults such sensor malfunction and actuator failure which provide great deviation of the residual signals and softer faults such as performance degradation and fluid leaks in the tanks and pipes. Faults of a smaller magnitude are captured very well albeit within a larger time range. The performance of the Fault Diagnosis and Identification was further improved by the implementation of statistically evaluating the residual signal and by the development of automatic threshold determination. Identification of the location of the fault is managed by the use of mapping the possible fault permutations and the Kalman filter behaviour, this providing full discrimination between any faults present. Overall the Kalman filter based FDI developed provided positive results in capturing and identifying a system fault on the test-rig

Improving the Accuracy and Scope of Control-Oriented Vapor Compression Cycle System Models

The benefits of applying advanced control techniques to vapor compression cycle systems are well know. The main advantages are improved performance and efficiency, the achievement of which brings both economic and environmental gains. One of the most significant hurdles to the practical application of advanced control techniques is the development of a dynamic system level model that is both accurate and mathematically tractable. Previous efforts in control-oriented modeling have produced a class of heat exchanger models known as moving-boundary models. When combined with mass flow device models, these moving-boundary models provide an excellent framework for both dynamic analysis and control design. This thesis contains the results of research carried out to increase both the accuracy and scope of these system level models. The improvements to the existing vapor compression cycle models are carried out through the application of various modeling techniques, some static and some dynamic, some data-based and some physics-based. Semiempirical static modeling techniques are used to increase the accuracy of both heat exchangers and mass flow devices over a wide range of operating conditions. Dynamic modeling techniques are used both to derive new component models that are essential to the simulation of very common vapor compression cycle systems and to improve the accuracy of the existing compressor model. A new heat exchanger model that accounts for the effects of moisture in the air is presented. All of these model improvements and additions are unified to create a simple but accurate system level model with a wide range of application. Extensive model validation results are presented, providing both qualitative and quantitative evaluation of the new models and model improvements.Air Conditioning and Refrigeration Project 17

DYNAMIC BEHAVIOR OF OPERATING CREW IN COMPLEX SYSTEMS: AN OBJECT-BASED MODELING & SIMULATION APPROACH

High-risk environments such as the control room of Nuclear Power Plants are extremely stressful for the front line operators; during accidents and under high task load situations, the operators are solely responsible for the ultimate decision-making and control of such complex systems. Individuals working as a team constantly interact with each other and therefore introduce team related issues such as coordination, supervision and conflict resolution. The aggregate impact of multiple human errors inside communication and coordination loops in a team context can give rise to complex human failure modes and failure mechanisms. This research offers a model of operating crew as an interactive social unit and investigates the dynamic behavior of the team under upset situations through a simulation method. The domain of interest in this work is the class of operating crew environments that are subject to structured and regulated guidelines with formal procedures providing the core of their response to accident conditions. In developing the cognitive models for the operators and teams of operators, their behavior and relations, this research integrates findings from multiple disciplines such as cognitive psychology, human factors, organizational factors, and human reliability. An object-based modeling methodology is applied to represent system elements and different roles and behaviors of the members of the operating team. The proposed team model is an extended version of an existing cognitive model of individual operator behavior known as IDAC (Information, Decision, and Action in Crew context). Scenario generation follows DPRA (Dynamic Probabilistic Risk Assessment) methodologies. The method capabilities are demonstrated through building and simulating a simplified model of a steam/power generating plant. Different configurations of team characteristics and influencing factors have been simulated and compared. The effects of team factors and crew dynamics on system risk with main focus on team errors, associated causes and error management processes and their impact on team performance have been studied through a large number of simulation runs. The results are also compared with several theoretical models and empirical studies

Prioritized Anomaly Catalog Generation Using Model-Based Reasoning

Anomaly management—the detection, diagnosis, and resolution of anomalies in a system—is traditionally performed using experiential techniques which are quickly computed, but poorly structured. Newer model-based approaches are more systematic and higher performing but are computationally expensive, which is a particular challenge for execution in an operational environment. This paper builds on a novel system to pre-compute model-based anomaly symptoms to enable quick retrieval and diagnosis in operational settings. New additions to this system include a simplified model interface, anomaly likelihoods associated with each component, and easier interpretation of results. The implemented system has been used successfully to detect and diagnose anomalies in a baseline test circuit as well as in an operational satellite monitoring network. Results show that this approach is promising; with a thorough model, the diagnosis and resolution processes of anomaly management could be greatly improved for more complex remote systems such as university-operated nanosatellites and field robotic vehicles

Intelligent Engine Systems Work Element 1.3: Sub System Health Management

The objectives of this program were to develop health monitoring systems and physics-based fault detection models for engine sub-systems including the start, lubrication, and fuel. These models will ultimately be used to provide more effective sub-system fault identification and isolation to reduce engine maintenance costs and engine down-time. Additionally, the bearing sub-system health is addressed in this program through identification of sensing requirements, a review of available technologies and a demonstration of a demonstration of a conceptual monitoring system for a differential roller bearing. This report is divided into four sections; one for each of the subtasks. The start system subtask is documented in section 2.0, the oil system is covered in section 3.0, bearing in section 4.0, and the fuel system is presented in section 5.0

A DIGITAL TWIN MODEL-BASED SYSTEM ENGINEERING APPROACH TO FAILURE ANALYSIS FOR AN ENGINE SYSTEM

In every portion of a product’s life cycle, system failures can occur. The DOD and defense contractors use failure analysis methods such as Failure Modes and Effects Analysis (FMEA) and Fault Tree Analysis (FTA), which have successfully reduced maintenance downtime and lowered life cycle costs as a result of reducing failures during system operations. However, challenges can hinder the effectiveness of failure analysis and have not been fully addressed due to limitations of current failure analysis and root cause analysis methods. This thesis addresses two of the challenges: (1) incorrectly classified system failures and (2) lack of failure traceability in the system life cycle. A methodology is proposed that incorporates some elements of both FMEA and FTA into a digital twin (DT) by employing the MBSE tool Magic Systems of Systems Architecture (MSOSA) to aid in failure analysis. An MBSE model simulation using an example of an engine is presented to demonstrate the efficacy of the methodology. The results are shown in terms of system operational availability. This research concludes that the approach has potential in emulating the real system’s behavior and can offer a more accurate estimated result. However, due to semantic errors in modeling in MSOSA, the model was unable to generate accurate results as intended. The model’s semantic errors must be addressed before it can be validated by comparing the results from MBSE model and the corresponding real-world system.Civilian, ST Engineering Land Systems Ltd, SingaporeApproved for public release. Distribution is unlimited

Control of Autonomous Surface Vessel

This project report is the documentation of the development of an autonomous vessel which can be used in Search and Rescue Operations. The aim of the automation is to follow official searchpatterns used by the Danish Naval Home-Guard, by means of control systems. The goal of the project is to help prevent fatal drowning accidents by lowering the rescue-time in the Search and Rescue operations. For simplification, the modeling of the vessel is split into translational and rotational movement. The parameters for the models are determined experimentally by conducting isolated tests. Through bode plots and root locus, three controllers are developed for different functionalities; maintaining velocity, slowing down dependent on distance, and correcting heading. The velocity and distance controllers are implemented in a cascade system, where the distance is designed as a P-controller. Both the velocity and heading controllers are designed as PID to suppress disturbances and speed up the system. The success criteria for the automation was put up as completing the chosen search pattern without deviating more than 2.5 meters from the path. The vessel managed to complete the course by intersecting every point in the case, but failed to stay within the deviation zone. Although, if a more reasonable case had been chosen with softer turns, the system would fare significantly better.Este informe de proyecto es la documentación del desarrollo de una embarcación autónoma que puede utilizarse en operaciones de búsqueda y rescate. El objetivo de la automatización es seguir los patrones de búsqueda oficiales utilizados por la Guardia Naval danesa, mediante sistemas de control. El objetivo del proyecto es ayudar a prevenir accidentes mortales por ahogamiento reduciendo el tiempo de rescate en las operaciones de búsqueda y salvamento. Para simplificar, la modelización del buque se divide en movimiento de traslación y de rotación. Los parámetros de los modelos se determinan experimentalmente mediante la realización de pruebas aisladas. Mediante diagramas de bode y root locus, se desarrollan tres controladores para diferentes funcionalidades; mantener la velocidad, reducir la velocidad en función de la distancia y corregir el rumbo. Los controladores de velocidad y distancia se implementan en un sistema en cascada, donde la distancia se diseña como un controlador P. Tanto los controladores de velocidad como los de rumbo están diseñados como PID para suprimir las perturbaciones y acelerar el sistema. El criterio de éxito para la automatización se estableció como completar el patrón de búsqueda elegido sin desviarse más de 2,5 metros de la ruta. El buque consiguió completar el recorrido intersectando todos los puntos, pero no consiguió mantenerse dentro de la zona delimitada. Aunque, si se hubiera elegido un caso más razonable con giros más suaves, el sistema habría funcionado mucho mejor.Aquest informe de projecte és la documentació del desenvolupament d'una embarcació autònoma que es pot utilitzar en operacions de recerca i rescat. L'objectiu de l'automatització és seguir els patrons de la Guàrdia Naval danesa, mitjançant sistemes de control. La finalitat del projecte és ajudar a prevenir accidents mortals per ofegament reduint el temps de rescat en les operacions de recerca i rescat. Per simplificar, la modelització de la barca es divideix en moviment de translació i de rotació. Els paràmetres dels models es determinen experimentalment mitjançant la realització de proves aïllades. Mitjançant diagrames de bode i root locus, es desenvolupen tres controladors per diferents funcionalitats; mantenir la velocitat, reduir la velocitat en funció de la distància i corregir el rumb. Els controladors de velocitat i distància s'implementen en un sistema en cascada, on la distància es dissenya com un controlador P. Tant els controladors de velocitat com els de rumb estan dissenyats com PID per suprimir les pertorbacions i accelerar el sistema. El criteri d'èxit per l'automatització es va establir com completar el patró de recerca escollit sense desviar-se més de 2,5 metres de la ruta. L'embarcació va aconseguir completar el recorregut creuant tots els punts, però no va aconseguir mantenir-se dintre de la zona delimitada. Encara que si s'hagués escollit un cas més raonable amb girs més suaus, el sistema hauria funcionat molt millor