NLGA based Active Control in Aerospace: fault tolerability, disturbance rejection, and parameter estimation

A new control scheme has been presented in this thesis. Based on the NonLinear Geometric Approach, the proposed Active Control System represents a new way to see the reconfigurable controllers for aerospace applications. The presence of the Diagnosis module (providing the estimation of generic signals which, based on the case, can be faults, disturbances or system parameters), mean feature of the depicted Active Control System, is a characteristic shared by three well known control systems: the Active Fault Tolerant Controls, the Indirect Adaptive Controls and the Active Disturbance Rejection Controls. The standard NonLinear Geometric Approach (NLGA) has been accurately investigated and than improved to extend its applicability to more complex models. The standard NLGA procedure has been modified to take account of feasible and estimable sets of unknown signals. Furthermore the application of the Singular Perturbations approximation has led to the solution of Detection and Isolation problems in scenarios too complex to be solved by the standard NLGA. Also the estimation process has been improved, where multiple redundant measuremtent are available, by the introduction of a new algorithm, here called "Least Squares - Sliding Mode". It guarantees optimality, in the sense of the least squares, and finite estimation time, in the sense of the sliding mode. The Active Control System concept has been formalized in two controller: a nonlinear backstepping controller and a nonlinear composite controller. Particularly interesting is the integration, in the controller design, of the estimations coming from the Diagnosis module. Stability proofs are provided for both the control schemes. Finally, different applications in aerospace have been provided to show the applicability and the effectiveness of the proposed NLGA-based Active Control System.

Tecniche di fault tolerance in swarm robotics

Questa tesi presenta e discute le sfide per ottenere sistemi di swarm robotis affidabili e tolleranti ai guasti e quindi anche alcuni metodi per rilevare anomalie in essi, in modo tale che ipotetiche procedure per il recupero possano essere affrontate, viene sottolineata inoltre l’ importanza di un’ analisi qualitativa dei guasti.

Crete fault scarp point cloud data

This paper assesses the along strike variation of active bedrock fault scarps using long range terrestrial laser scanning (t-LiDAR) data in order to determine the distribution behaviour of scarp height and the subsequently calculate long term throw-rates. Five faults on Cretewhich display spectacular limestone fault scarps have been studied using high resolution digital elevation model (HRDEM) data. We scanned several hundred square metres of the fault system including the footwall, fault scarp and hanging wall of the investigated fault segment. The vertical displacement and the dip of the scarp were extracted every metre along the strike of the detected fault segment based on the processed HRDEM. The scarp variability was analysed by using statistical and morphological methods. The analysis was done in a geographical information system (GIS) environment. Results show a normal distribution for the scanned fault scarp's vertical displacement. Based on these facts, the mean value of height was chosen to define the authentic vertical displacement. Consequently the scarp can be divided into above, below and within the range of mean (within one standard deviation) and quantify the modifications of vertical displacement. Therefore, the fault segment can be subdivided into areas which are influenced by external modification like erosion and sedimentation processes. Moreover, to describe and measure the variability of vertical displacement along strike the fault, the semi-variance was calculated with the variogram method. This method is used to determine how much influence the external processes have had on the vertical displacement. By combining of morphological and statistical results, the fault can be subdivided into areas with high external influences and areas with authentic fault scarps, which have little or no external influences. This subdivision is necessary for long term throw-rate calculations, because without this differentiation the calculated rates would be misleading and the activity of a fault would be incorrectly assessed with significant implications for seismic hazard assessment since fault slip rate data govern the earthquake recurrence. Furthermore, by using this workflow areas with minimal external influences can be determined, not only for throw-rate calculations, but also for determining samples sites for absolute dating techniques such as cosmogenic nuclide dating. The main outcomes of this study include: i) there is no direct correlation between the fault's mean vertical displacement and dip (R² less than 0.31); ii) without subdividing the scanned scarp into areas with differing amounts of external influences, the along strike variability of vertical displacement is ±35%; iii) when the scanned scarp is subdivided the variation of the vertical displacement of the authentic scarp (exposed by earthquakes only) is in a range of ±6% (the varies depending on the fault from 7 to 12%); iv) the calculation of the long term throw-rate (since 13 ka) for four scarps in Crete using the authentic vertical displacement is 0.35 ± 0.04 mm/yr at Kastelli 1, 0.31 ± 0.01 mm/yr at Kastelli 2, 0.85 ± 0.06 mm/yr at the Asomatos fault (Sellia) and 0.55 ± 0.05 mm/yr at the Lastros fault.

Enhanced Failure Detection Mechanism in MapReduce

The popularity of MapReduce programming model has increased interest in the research community for its improvement. Among the other directions, the point of fault tolerance, concretely the failure detection issue seems to be a crucial one, but that until now has not reached its satisfying level. Motivated by this, I decided to devote my main research during this period into having a prototype system architecture of MapReduce framework with a new failure detection service, containing both analytical (theoretical) and implementation part. I am confident that this work should lead the way for further contributions in detecting failures to any NoSQL App frameworks, and cloud storage systems in general.

S-SETA: Selective Software-Only Error-Detection Technique Using Assertions

Software-based techniques offer several advantages to increase the reliability of processor-based systems at very low cost, but they cause performance degradation and an increase of the code size. To meet constraints in performance and memory, we propose SETA, a new control-flow software-only technique that uses assertions to detect errors affecting the program flow. SETA is an independent technique, but it was conceived to work together with previously proposed data-flow techniques that aim at reducing performance and memory overheads. Thus, SETA is combined with such data-flow techniques and submitted to a fault injection campaign. Simulation and neutron induced SEE tests show high fault coverage at performance and memory overheads inferior to the state-of-the-art.

Fault diagnosis of an automotive suspension system

With the development of the embedded application and driving assistance systems, it becomes relevant to develop parallel mechanisms in order to check and to diagnose these new systems. In this thesis we focus our research on one of this type of parallel mechanisms and analytical redundancy for fault diagnosis of an automotive suspension system. We have considered a quarter model car passive suspension model and used a parameter estimation, ARX model, method to detect the fault happening in the damper and spring of system. Moreover, afterward we have deployed a neural network classifier to isolate the faults and identifies where the fault is happening. Then in this regard, the safety measurements and redundancies can take into the effect to prevent failure in the system. It is shown that The ARX estimator could quickly detect the fault online using the vertical acceleration and displacement sensor data which are common sensors in nowadays vehicles. Hence, the clear divergence is the ARX response make it easy to deploy a threshold to give alarm to the intelligent system of vehicle and the neural classifier can quickly show the place of fault occurrence.

The design of fault tolerant software for loosely coupled distributed systems

Requirements for systems to continue to operate satisfactorily in the presence of faults has led to the development of techniques for the construction of fault tolerant software. This thesis addresses the problem of error detection and recovery in distributed systems which consist of a set of communicating sequential processes. A method is presented for the `a priori' design of conversations for this class of distributed system. Petri nets are used to represent the state and to solve state reachability problems for concurrent systems. The dynamic behaviour of the system can be characterised by a state-change table derived from the state reachability tree. Systematic conversation generation is possible by defining a closed boundary on any branch of the state-change table. By relating the state-change table to process attributes it ensures all necessary processes are included in the conversation. The method also ensures properly nested conversations. An implementation of the conversation scheme using the concurrent language occam is proposed. The structure of the conversation is defined using the special features of occam. The proposed implementation gives a structure which is independent of the application and is independent of the number of processes involved. Finally, the integrity of inter-process communications is investigated. The basic communication primitives used in message passing systems are seen to have deficiencies when applied to systems with safety implications. Using a Petri net model a boundary for a time-out mechanism is proposed which will increase the integrity of a system which involves inter-process communications.

Wavelet packet decomposition-based fault diagnosis scheme for SRM drives with a single current sensor

Power converters are a key, but vulnerable component in switched reluctance motor (SRM) drives. In this paper, a new fault diagnosis scheme for SRM converters is proposed based on the wavelet packet decomposition (WPD) with a dc-link current sensor. Open- and short-circuit faults of the power switches in an asymmetrical half-bridge converter are analyzed in details. In order to obtain the fault signature from the phase currents, two pulse-width modulation signals with phase shift are injected into the lower-switches of the converter to extract the excitation current, and the WPD algorithm is then applied to the detected currents for fault diagnosis. Moreover, a discrete degree of the wavelet packet node energy is chosen as the fault coefficient. The converter faults can be diagnosed and located directly by determining the changes in the discrete degree from the detected currents. The proposed scheme requires only one current sensor in the dc link, while conventional methods need one sensor for each phase or additional detection circuits. The experimental results on a 750-W three-phase SRM are presented to confirm the effectiveness of the proposed fault diagnosis scheme.

Process Monitoring and Defect Detection of Additive Manufacturing Using Inline Coherent Imaging

With applications ranging from aerospace to biomedicine, additive manufacturing (AM) has been revolutionizing the manufacturing industry. The ability of additive techniques, such as selective laser melting (SLM), to create fully functional, geometrically complex, and unique parts out of high strength materials is of great interest. Unfortunately, despite numerous advantages afforded by this technology, its widespread adoption is hindered by a lack of on-line, real time feedback control and quality assurance techniques. In this thesis, inline coherent imaging (ICI), a broadband, spatially coherent imaging technique, is used to observe the SLM process in 15 - 45 $\mu m$ 316L stainless steel. Imaging of both single and multilayer builds is performed at a rate of 200 $kHz$, with a resolution of tens of microns, and a high dynamic range rendering it impervious to blinding from the process beam. This allows imaging before, during, and after laser processing to observe changes in the morphology and stability of the melt. Galvanometer-based scanning of the imaging beam relative to the process beam during the creation of single tracks is used to gain a unique perspective of the SLM process that has been so far unobservable by other monitoring techniques. Single track processing is also used to investigate the possibility of a preliminary feedback control parameter based on the process beam power, through imaging with both coaxial and 100 $\mu m$ offset alignment with respect to the process beam. The 100 $\mu m$ offset improved imaging by increasing the number of bright A-lines (i.e. with signal greater than the 10 $dB$ noise floor) by 300\%. The overlap between adjacent tracks in a single layer is imaged to detect characteristic fault signatures. Full multilayer builds are carried out and the resultant ICI images are used to detect defects in the finished part and improve upon the initial design of the build system. Damage to the recoater blade is assessed using powder layer scans acquired during a 3D build. The ability of ICI to monitor SLM processes at such high rates with high resolution offers extraordinary potential for future advances in on-line feedback control of additive manufacturing.

The Lea Grating Test In Assessing Detection Grating Acuity In Normal Infants Less Than 4 Months Of Age.

To assess binocular detection grating acuity using the LEA GRATINGS test to establish age-related norms in healthy infants during their first 3 months of life. In this prospective, longitudinal study of healthy infants with clear red reflex at birth, responses to gratings were measured at 1, 2, and 3 months of age using LEA gratings at a distance of 28 cm. The results were recorded as detection grating acuity values, which were arranged in frequency tables and converted to a one-octave scale for statistical analysis. For the repeated measurements, analysis of variance (ANOVA) was used to compare the detection grating acuity results between ages. A total of 133 infants were included. The binocular responses to gratings showed development toward higher mean values and spatial frequencies, ranging from 0.55 ± 0.70 cycles per degree (cpd), or 1.74 ± 0.21 logMAR, in month 1 to 3.11 ± 0.54 cpd, or 0.98 ± 0.16 logMAR, in month 3. Repeated ANOVA indicated differences among grating acuity values in the three age groups. The LEA GRATINGS test allowed assessment of detection grating acuity and its development in a cohort of healthy infants during their first 3 months of life.

Determination Of Tetrakis(hydroxymethyl)phosphonium Sulfate In Commercial Formulations And Cooling Water By Capillary Electrophoresis With Contactless Conductivity Detection.

A novel capillary electrophoresis method using capacitively coupled contactless conductivity detection is proposed for the determination of the biocide tetrakis(hydroxymethyl)phosphonium sulfate. The feasibility of the electrophoretic separation of this biocide was attributed to the formation of an anionic complex between the biocide and borate ions in the background electrolyte. Evidence of this complex formation was provided by (11) B NMR spectroscopy. A linear relationship (R(2) = 0.9990) between the peak area of the complex and the biocide concentration (50-900 μmol/L) was found. The limit of detection and limit of quantification were 15.0 and 50.1 μmol/L, respectively. The proposed method was applied to the determination of tetrakis(hydroxymethyl)phosphonium sulfate in commercial formulations, and the results were in good agreement with those obtained by the standard iodometric titration method. The method was also evaluated for the analysis of tap water and cooling water samples treated with the biocide. The results of the recovery tests at three concentration levels (300, 400, and 600 μmol/L) varied from 75 to 99%, with a relative standard deviation no higher than 9%.

Human Herpesvirus Infections Of The Central Nervous System: Laboratory Diagnosis Based On Dna Detection By Nested Pcr In Plasma And Cerebrospinal Fluid Samples.

Infections of the central nervous systems (CNS) present a diagnostic problem for which an accurate laboratory diagnosis is essential. Invasive practices, such as cerebral biopsy, have been replaced by obtaining a polymerase chain reaction (PCR) diagnosis using cerebral spinal fluid (CSF) as a reference method. Tests on DNA extracted from plasma are noninvasive, thus avoiding all of the collateral effects and patient risks associated with CSF collection. This study aimed to determine whether plasma can replace CSF in nested PCR analysis for the detection of CNS human herpesvirus (HHV) diseases by analysing the proportion of patients whose CSF nested PCR results were positive for CNS HHV who also had the same organism identified by plasma nested PCR. In this study, CSF DNA was used as the gold standard, and nested PCR was performed on both types of samples. Fifty-two patients with symptoms of nervous system infection were submitted to CSF and blood collection. For the eight HHV, one positive DNA result-in plasma and/or CSF nested PCR-was considered an active HHV infection, whereas the occurrence of two or more HHVs in the same sample was considered a coinfection. HHV infections were positively detected in 27/52 (51.9%) of the CSF and in 32/52 (61.5%) of the plasma, difference not significant, thus nested PCR can be performed on plasma instead of CSF. In conclusion, this findings suggest that plasma as a useful material for the diagnosis of cases where there is any difficulty to perform a CSF puncture.

Detection Of Explosives On The Surface Of Banknotes By Raman Hyperspectral Imaging And Independent Component Analysis.

The aim of this study was to develop a methodology using Raman hyperspectral imaging and chemometric methods for identification of pre- and post-blast explosive residues on banknote surfaces. The explosives studied were of military, commercial and propellant uses. After the acquisition of the hyperspectral imaging, independent component analysis (ICA) was applied to extract the pure spectra and the distribution of the corresponding image constituents. The performance of the methodology was evaluated by the explained variance and the lack of fit of the models, by comparing the ICA recovered spectra with the reference spectra using correlation coefficients and by the presence of rotational ambiguity in the ICA solutions. The methodology was applied to forensic samples to solve an automated teller machine explosion case. Independent component analysis proved to be a suitable method of resolving curves, achieving equivalent performance with the multivariate curve resolution with alternating least squares (MCR-ALS) method. At low concentrations, MCR-ALS presents some limitations, as it did not provide the correct solution. The detection limit of the methodology presented in this study was 50μgcm(-2).

A screening method for detection of hexavalent chromium levels in soils

A rapid and low cost method to determine Cr(VI) in soils based upon alkaline metal extraction at room temperature is proposed as a semi-quantitative procedure to be performed in the field. A color comparison with standards with contents of Cr(VI) in the range of 10 to 150 mg kg-1 was used throughout. For the different types of soils studied, more than 75% of the fortified soluble Cr(VI) were recovered for all levels of spike tested for both the proposed and standard methods. Recoveries of 83 and 99% were obtained for the proposed and the standard methods, respectively, taking into account the analysis of a heavily contaminated soil sample.

Histopathological events and detection of Metarhizium anisopliae using specific primers in infected immature stages of the fruit fly Anastrepha fraterculus (Wiedemann, 1830) (Diptera: Tephritidae)

The fungus Metarhizium anisopliae is used on a large scale in Brazil as a microbial control agent against the sugar cane spittlebugs, Mahanarva posticata and M. fimbriolata (Hemiptera., Cercopidae). We applied strain E9 of M. anisopliae in a bioassay on soil, with field doses of conidia to determine if it can cause infection, disease and mortality in immature stages of Anastrepha fraterculus, the South American fruit fly. All the events were studied histologically and at the molecular level during the disease cycle, using a novel histological technique, light green staining, associated with light microscopy, and by PCR, using a specific DNA primer developed for M. anisopliae capable to identify Brazilian strains like E9. The entire infection cycle, which starts by conidial adhesion to the cuticle of the host, followed by germination with or without the formation of an appressorium, penetration through the cuticle and colonisation, with development of a dimorphic phase, hyphal bodies in the hemocoel, and death of the host, lasted 96 hours under the bioassay conditions, similar to what occurs under field conditions. During the disease cycle, the propagules of the entomopathogenic fungus were detected by identifying DNA with the specific primer ITSMet: 5' TCTGAATTTTTTATAAGTAT 3' with ITS4 (5' TCCTCCGCTTATTGATATGC 3') as a reverse primer. This simple methodology permits in situ studies of the infective process, contributing to our understanding of the host-pathogen relationship and allowing monitoring of the efficacy and survival of this entomopathogenic fungus in large-scale applications in the field. It also facilitates monitoring the environmental impact of M. anisopliae on non-target insects.