Towards diagnosing hybrid systems

This paper reports on the findings of an on-going project to investigate techniques to diagnose complex dynamical systems that are modeled as hybrid systems. In particular, we examine continuous systems with embedded supervisory controllers which experience abrupt, partial or full failure of component devices. The problem we address is: given a hybrid model of system behavior, a history of executed controller actions, and a history of observations, including an observation of behavior that is aberrant relative to the model of expected behavior, determine what fault occurred to have caused the aberrant behavior. Determining a diagnosis can be cast as a search problem to find the most likely model for the data. Unfortunately, the search space is extremely large. To reduce search space size and to identify an initial set of candidate diagnoses, we propose to exploit techniques originally applied to qualitative diagnosis of continuous systems. We refine these diagnoses using parameter estimation and model fitting techniques. As a motivating case study, we have examined the problem of diagnosing NASA’s Sprint AERCam, a small spherical robotic camera unit with 12 thrusters that enable both linear and rotational motion.

Fault-tolerant formation driving mechanism designed for heterogeneous MAVs-UGVs groups

A fault-tolerant method for stabilization and navigation of 3D heterogeneous formations is proposed in this paper. The presented Model Predictive Control (MPC) based approach enables to deploy compact formations of closely cooperating autonomous aerial and ground robots in surveillance scenarios without the necessity of a precise external localization. Instead, the proposed method relies on a top-view visual relative localization provided by the micro aerial vehicles flying above the ground robots and on a simple yet stable visual based navigation using images from an onboard monocular camera. The MPC based schema together with a fault detection and recovery mechanism provide a robust solution applicable in complex environments with static and dynamic obstacles. The core of the proposed leader-follower based formation driving method consists in a representation of the entire 3D formation as a convex hull projected along a desired path that has to be followed by the group. Such an approach provides non-collision solution and respects requirements of the direct visibility between the team members. The uninterrupted visibility is crucial for the employed top-view localization and therefore for the stabilization of the group. The proposed formation driving method and the fault recovery mechanisms are verified by simulations and hardware experiments presented in the paper

Diagnosis of Fault Modes Masked by Control Loops with an Application to Autonomous Hovercraft Systems

This paper introduces a methodology for the design, testing and assessment of incipient failure detection techniques for failing components/systems of an autonomous vehicle masked or hidden by feedback control loops. It is recognized that the optimum operation of critical assets (aircraft, autonomous systems, etc.) may be compromised by feedback control loops by masking severe fault modes while compensating for typical disturbances. Detrimental consequences of such occurrences include the inability to detect expeditiously and accurately incipient failures, loss of control and inefficient operation of assets in the form of fuel overconsumption and adverse environmental impact. We pursue a systems engineering process to design, construct and test an autonomous hovercraft instrumented appropriately for improved autonomy. Hidden fault modes are detected with performance guarantees by invoking a Bayesian estimation approach called particle filtering. Simulation and experimental studies are employed to demonstrate the efficacy of the proposed methods

Model-based fault diagnosis for aerospace systems: a survey

http://pig.sagepub.com/content/early/2012/01/06/0954410011421717International audienceThis survey of model-based fault diagnosis focuses on those methods that are applicable to aerospace systems. To highlight the characteristics of aerospace models, generic nonlinear dynamical modeling from flight mechanics is recalled and a unifying representation of sensor and actuator faults is presented. An extensive bibliographical review supports a description of the key points of fault detection methods that rely on analytical redundancy. The approaches that best suit the constraints of the field are emphasized and recommendations for future developments in in-flight fault diagnosis are provided

Model based fault detection and isolation approach for actuator and sensor faults in a UAV

Thesis (MEng)--Stellenbosch University, 2021.ENGLISH ABSTRACT: This thesis presents the design and validation of model-based fault detection and isolation (FDI) approach for unmanned aerial vehicles (UAV). In safety-critical sys- tems such as chemical, nuclear plants and passenger aircraft, FDI is typically founded on hardware redundancy. In hardware redundancy, multiple actuators are spatially distributed to localise faults quickly, and sensor measurements are compared for consistency. The primary drawback with hardware redundancy is the increased installation complexity, weight, and costs. With modern computing technologies, model-based FDI offers a cost-effective, iterative and efficient FDI design process, verifiable with high fidelity computer-aided simulation (CAS). This thesis investigates the application of the Two-Stage Kalman filter (TSKF) to the problem of FDI. The TSKF solves the main deficiencies faced with the aug- mented state Kalman filter (ASKF), namely, numerical instability in ill-conditioned systems, and computational inefficiency where large parameter vectors are aug- mented. The TSKF approach utilises two parallel reduced-order KFs to estimate the system state and the parameter vectors separately. The UAV’s two rudders are not "isolable" because they produce identical moments. A novel active FDI (AFDI) method is proposed to isolate rudder actuator faults. The FDI displays high noise sensitivity under the evere Dryden turbulence model, resulting in high false detection and missed detection rates. A novel adap- tive technique is proposed to improve the robustness and sensitivity of the FDI. Unlike most methods which rely on a single scaling factor, the proposed adaptation technique employs multiple factors to weight the spread of fault parameter covari- ance matrix in the direction of flow of information, resulting in selective adaptation. Fault parameter variations are nonuniform in time and space. A static alarm threshold will induce high false alarms or missed alarms when set to low or too high, respectively. A novel adaptive threshold based on the normalised innovation squared (NIS) is proposed. A Monte Carlo campaign is carried out to validate the FDI while fault-sizes, the aircraft’s physical parameters, and disturbances are scat- tered, each with a distinct mean dispersion. The proposed strategy exhibits high robustness to noise and sensitivity to faults which indicates a reliable FDI.AFRIKAANSE OPSOMMING: Hierdie tesis beskryf die ontwerp en validering van ‘n model-gebaseerde foutop- sporing en isolasie (“fault deteciton and isolation (FDI)”) tegniek vir onbemande lugvoertuie (“unmanned aerial vehicles (UAVs)”). In veiligheidskritieke stelsels soos chemiese aanlegte, kernkragaanlegte, en passasiersvliegtuie, word FDI gewoon- lik gebaseer op hardeware-oortolligheid. Vir hardeware-oortolligheid word verskeie aktueerders ruimtelik versprei om foute vinnig op te spoor, en sensormetings word vergelyk vir ooreenstemming. Die primêre nadeel van hardeware-oortolligheid is die verhoogde installasie-kompleksiteit, gewig en koste. Met moderne rekenaarteg- nologieë bied model-gebaseerde FDI ’n koste-effektiewe, iteratiewe en doeltref-fende FDI-ontwerpproses met ‘n hoë betroubaarheid wat bevestig kan word met rekenaargesteunde simulasie. Hierdie tesis ondersoek die toepassing van die twee-stadium Kalman filter (“two- stage Kalman filter (TSKF)”) op die probleem van FDI. Die TSKF los die belangrik- ste tekortkominge van die uitgebredie-toestand Kalman-filter (“augmented state Kalman filter (ASKF)”) op, naamlik numeriese onstabiliteit in swak gekondisioneerde stelsels, en berekeningsondoeltreffendheid waar groot parametervektore bygevoeg word. Die TSKF-benadering gebruik twee parallelle Kalman filters met vermin- derde orde om die stelseltoestand en die parametervektore afsonderlik af te skat. Die UAV se twee roere (“rudders”) is egter nie “isoleerbaar” nie omdat dit hulle identiese draaimoment veroorsaak. ’n Nuwe aktiewe FDI-metode (AFDI) word voorgestel om die roeraktueerderfoute te isoleer. Die FDI vertoon hoë sensitiwiteit vir geraas vanaf erge turbulensie soos gemod- elleer deur die Dryden-turbulensie-model, wat lei tot ‘n groot aantal vals deteksies en gemiste deteksies. ’n Nuwe aanpassingstegniek word voorgestel om die robu- ustheid en sensitiwiteit van die FDI te verbeter. Anders as die meeste metodes wat op een enkele skaalfaktor staatmaak, gebruik die voorgestelde aanpassingstegniek verskeie faktore om die verspreiding van die foutparameterkovariansiematriks in die rigting van informasievloei te weeg, wat lei tot selektiewe aanpassing. Foutparametervariasies is nie eenvormig in tyd of ruimte nie. ’n Statiese alar- mdrempel sal hoë vals deteksies of gemiste deteksies veroorsaak as dit onderskei-delik óf te laag óf te hoog gestel is. ’n Nuwe aanpassingsdrempel wat gebaseer is op die genormaliseerde innovasie kwadraat (NIS) word voorgestel. ’n Monte Carlo simulasieveldtog is uitgevoer om die FDI te toets met die foutgroottes, die fisiese parameters van die vliegtuig, en die steurings lukraak gevarieer elk met ’n duide- like gemiddelde verspreiding. Die voorgestelde strategie vertoon ’n hoë robuus- theid vir geraas en sensitiwiteit vir foute, wat dui op ’n betroubare FDI

Autonomous Flight, Fault, and Energy Management of the Flying Fish Solar-Powered Seaplane.

The Flying Fish autonomous unmanned seaplane is designed and built for persistent ocean surveillance. Solar energy harvesting and always-on autonomous control and guidance are required to achieve unattended long-term operation. This thesis describes the Flying Fish avionics and software systems that enable the system to plan, self-initiate, and autonomously execute drift-flight cycles necessary to maintain a designated watch circle subject to environmentally influenced drift. We first present the avionics and flight software architecture developed for the unique challenges of an autonomous energy-harvesting seaplane requiring the system to be: waterproof, robust over a variety of sea states, and lightweight for flight. Seaplane kinematics and dynamics are developed based on conventional aircraft and watercraft and upon empirical flight test data. These models serve as the basis for development of flight control and guidance strategies which take the form of a cyclic multi-mode guidance protocol that smoothly transitions between nested gain-scheduled proportional-derivative feedback control laws tuned for the trim conditions of each flight mode. A fault-tolerant airspeed sensing system is developed in response to elevated failure rates arising from pitot probe water ingestion in the test environment. The fault-tolerance strategy utilizes sensor characteristics and signal energy to combine redundant sensor measurements in a weighted voting strategy, handling repeated failures, sensor recovery, non-homogenous sensors, and periods of complete sensing failure. Finally, a graph-based mission planner combines models of global solar energy, local ocean-currents, and wind with flight-verified/derived aircraft models to provide an energy-aware flight planning tool. An NP-hard asymmetric multi-visit traveling salesman planning problem is posed that integrates vehicle performance and environment models using energy as the primary cost metric. A novel A* search heuristic is presented to improve search efficiency relative to uniform cost search. A series of cases studies are conducted with surface and airborne goals for various times of day and for multi-day scenarios. Energy-optimal solutions are identified except in cases where energy harvesting produces multiple comparable-cost plans via negative-cost cycles. The always-on cyclic guidance/control system, airspeed sensor fault management algorithm, and the nested-TSP heuristic for A* are all critical innovation required to solve the posed research challenges.Ph.D.Aerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91453/1/eubankrd_1.pd

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

Autonomous Trajectory Planning and Guidance Control for Launch Vehicles

This open access book highlights the autonomous and intelligent flight control of future launch vehicles for improving flight autonomy to plan ascent and descent trajectories onboard, and autonomously handle unexpected events or failures during the flight. Since the beginning of the twenty-first century, space launch activities worldwide have grown vigorously. Meanwhile, commercial launches also account for the booming trend. Unfortunately, the risk of space launches still exists and is gradually increasing in line with the rapidly rising launch activities and commercial rockets. In the history of space launches, propulsion and control systems are the two main contributors to launch failures. With the development of information technologies, the increase of the functional density of hardware products, the application of redundant or fault-tolerant solutions, and the improvement of the testability of avionics, the launch losses caused by control systems exhibit a downward trend, and the failures induced by propulsion systems become the focus of attention. Under these failures, the autonomous planning and guidance control may save the missions. This book focuses on the latest progress of relevant projects and academic studies of autonomous guidance, especially on some advanced methods which can be potentially real-time implemented in the future control system of launch vehicles. In Chapter 1, the prospect and technical challenges are summarized by reviewing the development of launch vehicles. Chapters 2 to 4 mainly focus on the flight in the ascent phase, in which the autonomous guidance is mainly reflected in the online planning. Chapters 5 and 6 mainly discuss the powered descent guidance technologies. Finally, since aerodynamic uncertainties exert a significant impact on the performance of the ascent / landing guidance control systems, the estimation of aerodynamic parameters, which are helpful to improve flight autonomy, is discussed in Chapter 7. The book serves as a valuable reference for researchers and engineers working on launch vehicles. It is also a timely source of information for graduate students interested in the subject