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DESIGN AND ANALYSIS OF LINEAR AND NONLINEAR FILTERS FOR THE FDI OF AIRCRAFT MODEL SENSORS
No full textIncreasing demands on reliability for safety critical systems such as aircraft or spacecraft
require robust control and fault diagnosis capabilities as these systems are potentially
subjected to unexpected anomalies and faults in actuators, input-output sensors, components,
or subsystems. Consequently, fault diagnosis capabilities and requirements for
aerospace applications have recently been receiving a great deal of attention in the research
community.
A fault diagnosis system needs to detect and isolate the presence and location of the
faults, on the basis also of the control system architectures. Development of appropriate
techniques and solutions for these tasks are known as the fault detection and isolation
(FDI) problem. Several procedures for sensor FDI applied to a nonlinear simulated model
of a commercial aircraft, in the presence of wind gust disturbances and measurement
errors, are presented in this thesis.
The main contributions of this work are related to the design and the optimisation of
two FDI schemes based on a linear polynomial method (PM) and the nonlinear geometric
approach (NLGA). In the NLGA framework, two further FDI techniques are developed;
the first one relies on adaptive filters (NLGA–AF), whilst the second one exploits particle
filters (NLGA–PF).
The suggested design approaches leads to dynamic filters, the so–called residual generators,
that achieve both disturbance decoupling and robustness properties with respect
to modelling errors and noise. Moreover, the obtained results highlight a good trade-off
between solution complexity and achieved performances.
The FDI strategies are applied to the aircraft model in flight conditions characterised
by tight–coupled longitudinal and lateral dynamics. The robustness and the reliability
properties of the residual generators related to the considered FDI techniques are investigated
and verified by simulating a general aircraft reference trajectory.
Extensive simulations exploiting the Monte–Carlo analysis tool are also used for assessing
the overall performance capabilities of the developed FDI schemes in the presence of
both measurement and modelling errors. Comparisons with other disturbance–decoupling
methods for FDI based on neural networks (NN) and unknown input Kalman filter (UIKF)
are finally reported
GRAPHICAL USER INTERFACE SOFTWARE FOR AUTOMATIC DYNAMIC SYSTEM IDENTIFICATION, FAULT DIAGNOSIS AND FAULT TOLERANT CONTROL IN COMPLEX DISTRIBUTED PROCESSES
No full textThe increasing use of automation has generated interest in more sophisticated and intelligent systems. The main requirement for any manufacturing or process control system is to ensure reliable and continuous operation. Faults or failures can cause unacceptable danger or undesirable economic consequences. There is therefore great interest in the development of Fault Diagnosis Tolerant Control (FTC) systems, which undergo graceful degradation when faults arise. This enables human or automatic systems to put in place corrective measures before the system fails totally. High levels of reliability, maintainability and performance are now needed to ensure safe operation in hazardous human or environmental situations. The consequences of faults and failures in flight controls, chemical plants, nuclear plants, vehicle systems etc. are well known. The fault diagnosis function is one of the critical elements in a fault-tolerant control system. In general, the design of a fault tolerant control system consists of two different stages, regarding the design of the Fault Detection and Isolation system (the well-known FDI) and the design of the Fault Tolerant control unit (FTC).
The research activity concerning the fault detection and isolation problem strictly regards the development of dynamic systems (the so-called filters) in order to generate signals (the so-called residual) from which it is possible to detect any fault occurrence (fault detection stage) and to determine the system component affected by the fault (fault isolation task).
In the current literature, many different FDI and FTC tools and methods can be employed for more reliable control, fault monitoring and diagnosis systems. In particular, the detection, isolation and diagnosis of fault conditions in process or manufacturing systems can be considered from two perspectives. The first approach is to use control engineering theory and ``quantitative modelling''. The second method is to employ ``qualitative'' modelling and reasoning based on techniques developed within the artificial intelligence community. This includes techniques such as fuzzy logic, neural networks, neuro-fuzzy systems and model-based systems. Moreover, failure detection algorithms normally use hardware techniques or analytical redundancy to determine anomalies in the system behaviour. A first model-based consists of employing analytic redundancy which involves the use of the functional relationships between measured variables to provide a crosschecking test. Additional equipment may not be needed in such a circumstance, since existing measurements are simply used to provide estimates of other variables. A residual signal is defined based upon the difference generated from consistency checks. The residual will be of value zero during normal operation and will diverge from zero in the presence of fault conditions. This type of approach relies upon the use of a model and therefore falls under the category of model-based fault diagnosis methods. An alternative approach to fault diagnosis is to use the so-called hardware redundancy. A voting method is often used for hardware redundancy checking but this involves the duplication of physical devices, which is expensive. Multiple sensors can be used with the voting method and the outputs of these sensors can be compared to check for discrepancies between the measured signals. This solution, that can be expensive, allows to achieve more reliable performances than analytical redundancy schemes since does not rely on a perfect knowledge of a system model which, is some circumstances, can not be easy to obtain. On the other hand, the main advantage of model-based FDI algorithms is that additional sensors are often not required.
When the fault has been detected, the fault tolerant control system requires a fault accommodation algorithm. In particular, the current literature presents two main approaches. The first scheme is based on an ``explicit'' controller reconfiguration, while the second one provides for an ``implicit'' reconfiguration. In particular, the first approach requires the design of several controllers designed on the basis of different faulty model operations, which are discriminated by a supervision unit (sometimes it is referred as ``control falsification''). The FDI unit performs the fault falsification stage after the fault identification by means of a switching control scheme. On the other hand, the second approach is based on the design of a controller that has to be ``robust'' with respect to any fault occurrence. In this case, the controller reconfiguration is achieved from a robust point of view. Using several approaches, such as classical adaptive control schemes, neuro-fuzzy systems and the theory of non-linear regulators, can perform the design of a robust controller.
It is worthwhile noting that one of the most important aspects of the control design has been neglected by the current literature. This problem concerns the safety of the control system design and its application to large-scale processes (distributed systems). These systems, which are important from a practical point of view, are critical to deal with due to the high number of process variables, components and connections present in the system generating the so-called fault propagation phenomenon. The study of the FDI and FTC units cannot be performed locally, and the possible connections among the different components have to be taken into account during the system analysis stage. The main goal consists of defining mathematical methods and schemes able to describe the whole distributed system, in order to manage the FDI, the FTC, the reconfiguration, the supervision and the reliability problems for whole system. Only few contributions addressing these topics can be found in the current literature, even if important theoretic and practical subjects are still open and can be investigated
Fault Diagnosis for Aircraft System Models: An Introduction from Fault Detection to Fault Tolerance
No full textSafety in aircraft systems is a concern of rising importance, especially due to the sophisticated control devices exploited to improve the overall system performance, including both digital designs and complex hardware (input-output sensors, actuators, and components). Thus, control systems must include automatic supervision tasks to diagnose incipient malfunctions, as early as possible. This book focuses on the design of robust linear and nonlinear dynamic filters, obtained via model-based and analytical approaches for fault diagnosis and identification. The problem is treated in all its aspects covering: nonlinear modelling of aircraft systems; design of disturbance decoupled dynamic filters for residual generation; fault detection and estimation, fault tolerant control. Sample case studies are used to demonstrate the application of these techniques to high fidelity flight simulators. This book will be of interest to researchers in aircraft fault tolerant control, fault detection and diagnosis. Aircraft control engineers interested in applying the latest methods in fault detection and diagnosis will benefit from the simulation examples
Design of residual generators and adaptive filters for the FDI of aircraft model sensors
No full textThe main contribution of this paper is the description and application of a comprehensive set of
methodologies for fault detection and isolation (FDI) of aircraft sensors. In particular, a new nonlinear
geometric approach (NLGA) and an efficient linear polynomial method (PM) are presented and
compared, together with simulation results obtained from a commercial aircraft model. Adaptive filters
with disturbance decoupling for fault identification are designed via the developed NLGA-based
method. On the other hand, the FDI scheme based on linear PM exploits a disturbance decoupling
technique in connection with a linear dynamic filter design procedure. The FDI strategies are applied to
the aircraft simulator data in a flight condition characterised by tight–coupled longitudinal and lateral
dynamics. Moreover, in order to analyse robustness and reliability properties of the two FDI schemes,
extensive simulations are performed in the presence of turbulence, measurement noise and modelling
errors
Residual generator design for the FDI of linear multivariable sampled-data dynamic systems
No full textThis paper addresses the problem of the detection and isolation of the input and output sensor faults for a linear multivariable sampled-data dynamic system, in the presence of disturbance signals. In particular, this work proposes a polynomial approach for the design of residual generators in order to realise a complete diagnosis scheme when additive faults are present. It is shown that the use of an input- output description for the linear dynamic sampled-data model of the system under investigation allows to compute in a straightforward way the discrete-time residual generators. The residual generator design is performed in order to maximise a suitable fault sensitivity function. Thus, the suggested design approach leads to dynamic filters that achieve both disturbance de-coupling and desired transient properties in terms of a fault to residual reference transfer function. The results obtained in the simulation of the faulty behaviour of a discrete-time turbine jet engine model are finally reported
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Fault Diagnosis Techniques for Aircraft Simulated Model Sensors
No full textThis paper addresses the study and the application of a comprehensive set of
methodologies for fault detection and isolation of aircraft model input–output sensors. In
particular, a novel nonlinear approach and an efficient linear method are developed and analysed
with extensive simulation results obtained from a commercial aircraft model. The developed
nonlinear method exploits adaptive filters for fault identification with disturbance de–coupling
achieved via a nonlinear geometric approach. On the other hand, the linear filter design for
FDI is based on a polynomial method that allows also to achieve good disturbance de–coupling
properties. The FDI strategies are applied to the aircraft simulator data in a flight condition
characterised by tight–coupled longitudinal and lateral dynamics. Finally, the design reliability
of the two FDI schemes is assessed by means of extensive simulations in the presence of
turbulence, measurement noise and modelling errors
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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