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In this work, the problem of fault detection, isolation, and reconfiguration (FDIR) for Networked-Control Systems (NCS) of aerospace vehicles is discussed. The concept of fault-tolerance is introduced from a generic structure, and a review on quantitative and qualitative methods (state estimation, parameter estimation, parity space, statistic testing, neural networks, etc.) for FDIR is then performed. Afterwards, the use of networks as loop-closing elements is introduced, followed by a discussion on advantages (flexibility, energy demand, etc.) and challenges (networks effects on performance, closed-loop fault-effects on safety, etc.) represented thereby. Finally, examples of applications on aerospace vehicles illustrate the importance of the discussion herein exposed.

The architecture is a concept very broad and important that is directly connected to the realization of a system. It defines what the system is capable of doing, how it accomplishes its mission and how the system is. Currently, the development of system architectures is considered a domain of knowledge where science meets art. In some specific areas, the methods on the development of system architectures are already well formalized. However, when analyzing the evaluation of system architectures such as those for multi-domain control systems, it is clear that there is still much room for rationalization. In these cases, the search for new methods for the evaluation of system architectures is currently in the state of art. In this work we discuss methods used in the verification and validation of control systems architectures of cyber-physical systems based on models and systems metrics.

Cyber-physical systems are joint instances of growing complexity and high integration of elements in the information and physical domains reaching high levels of difficulty to engineer an operate them. This happens with satellites, aircraft, automobiles, smart grids and others. Current technologies as computation, communication and control integrate those domains to communicate, synchronize and operate together. However, the integration of different domains brings new challenges and adds new issues, mainly in real time distributed control systems, beginning with time synchronization. In this paper, we present a discussion on time synchronization and their effects in distributed cyber-physical control systems. To do that, we review the literature, discuss some time synchronization techniques used in cyber-physical systems, and illustrate them via model and simulation of a system representative of the aerospace area.

The increasing use of embedded electronics in aerospace and automotive vehicles increases the designers' concern regarding the reliability of the components as well as the reliability of their interconnections. The discussion about the most appropriate method for assessing the reliability of solder joints for a given application is an ever-present theme in the literature. Several methods of prediction have been developed for assessing the reliability of solder joints. The standard method established by the industries for assessing reliability of solder joints is the thermal cycling. However, when the thermal distributions in real applications are studied, particularly in some electronic components used in on-board electronics of space systems, the thermal cycling does not represent what actually happens in practice in the packaging.

Switching controls are those that can switch between control or plant modes to perform their functions. They have the advantage of being simpler to design than an equivalent control system with a single mode. However, the transients between those modes can introduce steps or overshootings in the state variables, and this can degrade the performance or even damage the control or the plant. So, the smoothing of such transients is vital for their reliability and mantainability. This is can be of extreme importance in the aerospace and automotive fields, plenty of switchings between manual and autopilot modes via relays, or among gears via clutches, for example. In this work, we present a first strategy for smoothing transients in switching controls of aerospace and automotive systems.

In this work we present a new procedure for customizing, in the desired format, requirements reports generated by a Requirements Engineering Environment. This environment includes tools for: 1- capturing textual and pictoric requirements; 2- templating requirements documents that can be adjustable to the formats required by the certification authorities or system engineering groups; 3- translating features from/to the main word processors used in the industry (Word, Excel, etc. formats); 4- managing requirements configuration. It provides gains of productivity, correctness, reusability, traceability, coverage, etc, improving the efficiency of the projects. The procedure emphasizes items 2 and 3, and is illustrated with some examples driven from the aerospace industry.

Currently, aerospace and automotive industries are developing complexand/or highly integrated systems, whose services require greater confidence to meet a set of specifications that are increasingly demanding, such as successfully operating a communications satellite, a commercial airplane, an automatic automobile, and so on. To meet these requirements and expectations, there is a growing need for fault treatment, up to predict faults and monitor the health of the components, equipment, subsystems or systems used. In the last decades, the approaches of 1) Fault Prevention, 2) Fault Detection/Tolerance and 3) Fault Detection/Correction have been widely studied and explored.

Resistance Spot Welding is a manufacturing process widely used in several industrial segments, such as automotive, electronics, aerospace and others. It stands out from other welding processes, as it does not require addition material to join parts. This type of process needs to be robust and reliable in order to ensure the quality of the welded joint produced, as any variation in the quality of the weld point can affect the functionality and safety of the final product. The resistance spot welding process uses different technologies and operating sequences that depend on various characteristics, factors and parameters. The combinations and values of these allow for numerous possibilities, making their adjustments time-consuming, costly and exhaustive, so it is necessary to apply statistical techniques to optimize the process. In the literature, it is possible to find several statistical techniques for the optimization of the process.

Current systems such as: satellites, aircrafts, automobiles, turbines, power controls and traffic controls are becoming increasingly complex and/or highly integrated as prescribed by the SAE-ARP-4754 Standard. Such systems and their control systems use many modes of operation and many forms of redundancy to achieve high levels of performance and high levels of reliability under changing environments and phases of their lifecycle. The environment disturbances, environment variability, plant non-linear dynamics, plant wear, plant faults, or the non-symmetric plant operation may cause de-synchronization in phase or time among: 1) simultaneous units in the same normal mode of operation; 2) successive units in successive normal modes of operation; 3) main and spare units from normal to faulty modes of operation. So, techniques to reduce those causes or their effects are becoming important aspects to consider in the design of such systems.

Current systems such as satellites, aircrafts, automobiles, turbines, power controls and traffic controls are becoming increasingly complex and/or highly integrated as prescribed by the SAE-ARP-4754a Standard. Such systems operate in a real time distributed environment which frequently requires a common knowledge of time among different devices, levels and granularities. So, temporal correctness is mostly needed, besides logical correctness. It can be achieved by hardware clocks and devices, software clocks and algorithms, or both, to avoid or tolerate, within appropriate margins, the time faults or failures that may occur in aerospace and automotive systems. This paper presents an overview of clock synchronization algorithms and their uses in aerospace and automotive systems. It is based on a review of the literature, discussion and comparison of some clock synchronization algorithms with different policies.

Real-time critical systems are those whose failures may cause loss of transactions/data, missions/batches, vehicles/properties, or even people/human life. Accordingly, some regulations prescribe their maximum acceptable probability of failures to range from about 10−4 to 10−10 failures per hour. Examples of such systems are the ones involving nuclear plants, aircrafts, satellites, automobiles, or traffic controls. They are becoming increasingly complex and/or highly integrated as prescribed by the SAE-ARP-4754A Standard. Those systems include, most of the time, real time critical software that must be specified, designed, implemented, validated, verified and accredited (VVA). To do that, models, specially the V-Model, are frequently adopted, together with methods and tools which perform software VVA to ensure compliance (of correctness, reliability, robustness, etc.) of software to several specific standards such as DO178-B/DO-178C (aviation) or IEC 26262 (automotive) among others.

The aerospace and automotive electronic systems are getting more complex and/or highly integrated, as defined by ARP 4754A, making extensive use of microelectronics and digital memories which, in turn, operates in higher frequencies and lower voltages. In addition, the aircraft are flying in higher altitudes, and polar routes are getting more frequent. These factors raise the probability of occurrence of hazardous effects like the Single Event Upsets in their embedded electronic systems. These must be designed in a way to tolerate and assure the immunity to the Single Event Upsets, based upon criteria such as reliability, availability and criticality. This paper proposes an overview of an assurance process of immunity of embedded electronic systems to Single Event Upsets caused by ionizing particles by means of a review of literature and an analysis of standards as ECSS-E-ST-10-1, NASA Single Event Effects Criticality Analysis and IEC TS 62396-1.

Internet of Things (IoT) for real-time applications are demanding more and more high performance, precision, accuracy, modularity, integration, dependability and other attributes in a complex and/or highly integrated environment. Such systems need to provide coordination among the integrated components (e.g. sensors, computer, controller and networks) for enabling the application to take real-time measurements and to translate into controllable, observable and smart actions with strict timing requirements. Therefore, coordination and synchronization are required to ensure the controllable, observable and smart actions of real-time IoT systems. This paper shows the design issues about the coordination and synchronization in the internet of things applied to real-time applications. We also show the current coordination and synchronization techniques and their design issues when applied to IoT systems.

Eigenstructure techniques allow to detect and isolate faulty components in a dynamic process, such as sensor biases, actuator malfunctions, changes in dynamic parameters due to leaks and deterioration. Fault detection is the first step to achieve fault tolerance, but for this the redundancy has to be included in the system. This redundancy can be either by hardware or by software. In situations in which it is not possible to use hardware redundancy only the software redundancy can be used. Therefore using eigenstructure techniques, for the fault detection and isolation, the tests can be done through the angle between the residue vector direction and the fault direction vector. By this way, we can reduce false alarm and the alarm loss rates due to the noise and changes in system parameters.

This work presents the identification of the longitudinal mode of an aircraft by using time and frequency response methods. To do this, the transfer function was identified based on the sampled response to a step input. The transfer function was validated comparing the model step response with the original system step response. The identification of the system transfer function was performed by using the Fast Fourier Transform (FFT) and Bode Graphs methods. The model validation quantification was performed by means of the mean quadratic-error method applied to the step response difference. Based on that, the identified model was considered to be quite representative, thus proving the suitability of the applied methods.

In this work we discuss some types of simulation architectures and standards, their characteristics and applications to the simulation and control of aerospace vehicles. This includes: the basic definitions, types and characteristics of simulators and simulations (physical, computational, hybrid, etc.; discrete events, discrete time, continuous time, etc; deterministic, stochastic, etc.) their basic compromise (simplicity x fidelity), their man-machine interfaces and interactions (virtual, constructive, live, etc.), their evolution law (time, events, mixed, etc.), their architectures (“stand-alone”, PIL, HIL, MIL, DIS, HLA, etc.), their standards (OMBA, SIMNET, ALSP, DIS, HLA 1.3, HLA 1516, ASIA, AP2633, etc.) and their applications to the simulation and control of aerospace vehicles. This is illustrated by some examples driven from the aerospace industry

In this work we discuss some types of simulation environments and laboratories, their characteristics and applications to the simulation and control of aerospace vehicles. This includes: the basic definitions, types and characteristics of simulators and simulations (physical, computational, hybrid, etc.; discrete events, discrete time, continuous time, etc; deterministic, stochastic, etc.) their basic compromise (simplicity × fidelity), their man-machine interfaces and interactions (virtual, constructive, live, etc.), their evolution law (time, events, mixed, etc.), their architectures (“stand-alone”, PIL, HIL, MIL, DIS, HLA, etc.), and especially, their environments (discrete, continuous, hybrid, etc.) and laboratories (physical, computational, hybrid, etc.), and their applications to the simulation and control of aerospace vehicles. This is illustrated by some examples driven from the aerospace industry.

In this work we discuss some types of simulators and simulations, their characteristics and applications to the simulation and control of aerospace vehicles. This includes: the basic definitions, types and characteristics of simulators and simulations (physical, computational, hybrid, etc.; discrete events, discrete time, continuous time, etc; deterministic, stochastic, etc.) their basic compromise (simplicity × fidelity), their man-machine interfaces and interactions (virtual, constructive, live, etc.), their evolution law (time, events, mixed, etc.), their architectures (“standalone”, PIL, HIL, MIL, DIS, HLA, etc.), their environments (discrete, continuous, hybrid, etc.) and their applications to the simulation and control of aerospace vehicles. This is illustrated by some examples driven from the aerospace industry

On several engineering applications high Reliability is one of the most wanted features. The aspects of Reliability play a key role in design projects of aircraft, spacecraft, automotive, medical, bank systems, and so, avoiding loss of life, property, or costly recalls. The highly reliable systems are designed to work continuously, even upon external threats and internal Failures. Very convenient is the fact that the term 'Failure' may have its meaning tailored to the context of interesting, as its general definition refers to it as "any deviation from the specified behavior of a system". The above-mentioned 'deviation' may refer to: performance degradation, operational misbehavior, deviation of environmental qualification levels, Safety hazards, etc. Nevertheless, Reliability is not the only requirement for a modern system. Other features as Availability, Integrity, Security and Safety are always part of the same technical specification, in a same level of importance.

This paper presents some techniques for fault diagnosis in aerospace and automotive systems. A diagnosis technique is an algorithm to detect and isolate fault components in a dynamic process, such as sensor biases, actuator malfunctions, leaks and equipment deterioration. Fault diagnosis is the first step to achieve fault tolerance, but the redundancy has to be included in the system. This redundancy can be either by hardware or software. In situations in which it is not possible to use hardware redundancy only the analytical redundancy approach can be used to design fault diagnosis systems. Methods based on analytical redundancy need no extra hardware, since they are based on mathematical models of the system.