Diagnosis of Icing and Actuator Faults in UAVs Using LPV Unknown Input Observers

This paper proposes a discrete-time linear parameter varying (LPV) unknown input observer (UIO) for the diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs). The proposed approach, which is suited to an implementation on-board, exploits a complete 6-degrees of freedom (DOF) UAV model, which includes the coupled longitudinal/lateral dynamics and the impact of icing. The LPV formulation has the advantage of allowing the icing diagnosis scheme to be consistent with a wide range of operating conditions. The developed theory is supported by simulations illustrating the diagnosis of actuator faults and icing in a small UAV. The obtained results validate the effectiveness of the proposed approach

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

Techniques for effective virtual sensor development and implementation with application to air data systems

1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen716. INGEGNERIA AEROSPAZIALEnoopenBrandl, Albert