Search Results

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.

Systems such as satellites, airplanes, cars and air traffic controls are becoming more complex and/or highly integrated. These systems integrate several technologies inside themselves, and must be able to work in very demanding environments, sometimes with few or none maintenance services due to their severe conditions of work. To survive such severe work conditions, the systems must present high levels of reliability, which are achieved through different approaches, processes, etc. These unfold in many: levels of aggregation (systems, subsystems, equipments, components, etc.), phases of their lifecycles (conception, design, manufacturing, assembly, integration, tests, operation, etc.), environments (land, sea, air, space, etc.), types of components/applications/experiences/technological communities (nuclear, aerospace, military, automotive, medical, commercial, etc.), leaded by the widespread use of semiconductors.

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.

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.

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.

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.

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.

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 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.

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.