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State observers employed in the analytical redundancy approach can generate redundant signals. As the sensor has noise in its measures, this noise also affects the redundant signal. In this paper, we will show how the noise in the sensor signal can affect the redundant signal, generated for a bank of observers in a DOS structure, and some simulations results of this signal and finally we will do some considerations in the state observers design to reduce the noise level at the redundant signals.

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 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.

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.

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 discuss current trends driving the aerospace and automotive systems architectures. This includes trends as: 1) pos-globalization and regionalization; 2) the formation of knowledge oligopolies; 3) commonality, standardization and even synergy (of components, tools, development process, certification agents, standards); 4) reuse and scalability; 5) synergy of knowledge and tools convergence; 6) time, cost and quality pressures and innovation speed; 7) environmental and safety issues; and 8) abundance of new technologies versus scarcity of skilled manpower to apply them.

Life-critical aeronautical projects are increasing their lifecycle up to the point where a product is developed to be available in the market for more than 70 years, but requiring daily service support and replacement parts. Therefore, unavailability of components or services can have a severe impact over the product through its lifecycle. In this work we study some causes of unavailability of components and services and their effects over the lifecycle of an aeronautical project, to propose recommendations, alternatives and actions to be taken in the early phases of project development to help mitigate such effects over the product lifecycle. To do that, we initially present the causes of unavailability of components and services. Then, we discuss some of their effects over the lifecycle of an aeronautical project.

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.

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.

The realization of modern systems subjected to automatic control, such as aircraft, automobiles, satellites, rocket launchers, cargo and military ships, and so forth; increasingly assume, within its very set of requirements, the task of providing better dependability, i.e.: safety, reliability, and availability altogether. Towards this demand, fault-tolerant control greatly meets such growing demand of dependability, by its ability of recognizing the occurrence of potentially hazardous/hazardous faults within the overall (closed-loop) system, and by taking remedial action whenever necessary/mandatory. The process of fault tolerance can be segregated into two fundamental steps: (1) that of fault diagnosis, comprising fault detection-isolation-identification, and, (2) control adjustment/reconfiguration. This paper focuses on the second step, of control adjustment/reconfiguration.

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.

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.

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.

In this work we discuss the fault avoidance and the fault tolerance approaches for increasing the reliability of aerospace and automotive systems. This includes: the basic definitions/concepts (reliability, maintainability, availability, redundancy, etc.), and characteristics (a priori analysis, a posteriori analysis, physical/hardware redundancy, analytical/software redundancy, etc.) of both approaches, their mathematical background and models (exponential, Weilbull, etc.), their basic theory, their methods and techniques (fault trees, dependence diagrams, Markov chains, etc.), some of their standards (SAE-ARP4761, AC 25.1309, etc.) and simulation environments (Cafta, etc.), and their applications to the reliability analysis and reliability improvement of aerospace and automotive vehicles. This is illustrated by some examples driven from the aerospace and automotive industries.