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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.

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.

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.

Control systems that can switch between control or plant modes have the advantage of being simpler to design than an equivalent system with a single mode. However, the transition between these modes can introduce steps or overshootings in the state variables, and this can degrade the performance or even damage the system. This is can be of extreme importance in fields such as aerospace and automobilistic, as the switching between manual and autopilot modes or the switching of gears In this work, we will use integral criteria in original ways, to determine a coefficient on the system which should optimize the trajectory of the control signal, during the switching between two modes. Effectively, each transition will be done by a subsystem specific for it, according to the selected criterion. The simulations will be made in MATRIXx, MatLab or both, using models chosen from aerospace or automobilistic fields.

With the growing complexity and integration of systems as satellites, automobiles, aircrafts, turbines, power controls and traffic controls, as prescribed by SAE-ARP-4754A Standard, the time de-synchronization can cause serious or even catastrophic failures. Time synchronization is a very important aspect to achieve high performance, reliability and determinism in networked control systems. Such systems operate in a real time distributed environment which frequently requires a consistent time view among different devices, levels and granularities. So, to guarantee high performance, reliability and determinism it is required a performance evaluation of time synchronization of the overall system. This time synchronization performance evaluation can be done in different ways, as experiments and/or model and simulation.

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.

The Multimission Platform (MMP) is a generic service module currently in Project at INPE. In the 2001 version, its control system can be switched between nine main Operation Modes and other submodes, according to information from satellite sensors and ground commands. The Nominal Mode stabilizes the MMP in three axes and takes it to a nominal attitude, using three reaction wheels. Each wheel has coarse and fine acquisition submodes. The use of multiple modes of control for specific situations frequently is simpler than projecting a single controller for all cases. However, besides being harder to warrant its general stability, the mere switching between these submodes generates bumps, which can reduce the performance and even damage the actuator or plant. In this work, we present an application of diverse methods to smooth the transition between control submodes of the Nominal Mode of the MMP.

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.

The supply of electrical power is one of the most important functions required by the diverse payloads of satellites. A fault in the corresponding subsystem might lead to mission or even vehicle loss. Among the causes of such faults, we highlight the phenomenon of thermal avalanche in batteries. It can be explained as an energetic unbalance where the rate of heat generated in the interior of the system exceeds its capacity to dissipate it. This occurred to the OAO1 of NASA just after its launch on April 8, 1966; and with the CBERS2 of CAST and INPE already in orbit in 2007 and 2009. This work presents a discussion on the causes and effects of thermal avalanches in artificial satellite battery charging and discharging systems.

Many control systems switch between control modes according to necessity. That is often simpler than designing a full control to all situations. However, this creates new problems, as determining the composed system stability and the transient during switching. The latter, while temporary, may introduce overshooting that degrade performance and damage the plant. This is particularly true for the MultiMission Platform (MMP), a generic service module currently under design at INPE. Its control system can be switched among nine main Modes of Operation and other submodes, according to ground command or information coming from the control system, mainly alarms. It can acquire one and three axis stabilization in generic attitudes, with actuators including magnetotorquers, thrusters and reaction wheels.

Current systems such as satellites, aircrafts, automobiles, turbines, wind power generators and traffic controls are becoming increasingly complex and/or highly integrated as prescribed by the SAE-ARP-4754 Standard. Such systems frequently require accurate generation, distribution and time or phase synchronization of signals with different frequencies that may be based on one reference signal and frequency. But the environment fluctuations or the non-linear dynamics of these operations cause uncertainties (skew and jitter) in the phase or time of the reference signal and its derived signals. So, techniques to reduce those causes or their effects are becoming important aspects to consider in the design of such systems. The PLL techniques are useful for establishing coherent phase or time references, jitter reduction, skew suppression, frequency synthesis, and clock recovery in numerous systems such as communication, wireless systems, digital circuits, rotors, and others.

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.

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 work presents the analysis, design and simulation of the reconfigurable control architecture for the contingency mode of the MultiMission Platform (MMP). The MMP is a generic service module currently under design at INPE. Its control system can be switched among nine main Modes of Operation and other Sub-Modes, according to ground command or information coming from the control system, mainly alarms. The implementation followed the specifications when they were found, otherwise it was designed. They cover operations from detumbling after launcher separation and solar acquisition, to achieving payload nominal attitude and orbital corrections maneuvers. The manager block of the control system was implemented as a finite state machine. The tests are based in simulations with the MatriX/SystemBuild software. They focused mainly on the worst cases that the satellite is supposed to endure in its mission, be it during modes or transitions between modes and submodes.

A major trend in modern aerospace and automotive systems is to integrate computing, communication and control into different levels of the vehicle and/or its supervision. A well fitted architecture adopted by this trend is the Common Bus Network Architecture. A Networked Control System (NCS) is called when the control loop is closed through a communication network. The presence of this communication network introduces new characteristics (sharing bus, delays, jitter etc.) to be considered at design time of a control system. This work focuses on the influences of data bus protocols on an aircraft Fly-By-Wire (FBW) networked control system. We intent to show, through simulations, the influences of sharing bus on a real time control system. To compare effects, we choose the CAN Bus protocol where the medium access control is event driven; and the TTP protocol where the medium access control is time driven.

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 study the stability of digital controls of flexible/Vibratory aerospace/automobile systems by the graph norm technique, occurring in sampled-data control systems due to sampling period variations. To do so, this work tries to establish regions (graphs) of stability and instability in a Banach Space, the distances (norms) between them and a given design to detect analytically and/or numerically its margins of stability or conditions of instability. Based on that, we sketch the first steps for a design methodology of stable digital controllers of flexible/vibratory systems embedded in a sampled-data system with adjustable sampling periods of A/D and D/A converters. A short tutorial about the graph norm technique is also given and some theoretical results as well numerical results are shown. This work was done in two folds to unmask the stability secrets hidden in a general sampled-data control system, until today not revelated.

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