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In this work we developed a comparative study between many resolution methods of the exponential matrix from an inequality extracted from a specific Liapunov function to obtain information about some stability regions for sampled-data control systems as a function of the sampling-time and the plant used. We used many methods from the literature like: power series, Cayley-Hamilton theorem, Lagrange-Sylvester theorem, eigenvalues/ eigenvectors decomposition and Padé rational approximation. The main objective of this study is to choose the most appropriate method for the resolution of this important problem and to use the results found as a basis for future works.

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.

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 paper presents an analytical and simulation study of the stabilization and improvement of the active vibration damping of a system modeled by a simple analog harmonic oscillator driven by discrete time control. Initially, this control is the Bilinear (or Tustin) s-z mapping equivalent of a continuous-time asymptotically stable Proportional plus Derivative (PD) control. It is tested with high values of the sampling period. It is shown that all classical mappings (Tustin, Schneider, etc.) tested may instabilize the system. To circumvent this, we propose and use a new (ST1) mapping that behaves better than the classical ones tested under the same conditions. We also model an active discrete control of a suspension of a vehicle, and compare the performance between the PD controllers designed by Bilinear and by the new (ST1) S-Z mappings, for this example.

The measure of time intervals with relatively high accuracy (of 1 milisecond, at least) in PC computers is a relatively hard task to solve. But this is essential for the digital simulation, with sensors in the loop, of fast control systems. This work allows the reading of the programmable internal timer 8253 present in a typical PC, reaching 1 ms resolution, at least, through a C high level language routine. The determination of the angular velocity of a 53M2-30H Contraves 3-axis dynamic simulator used in that simulation was improved by the use of this work, allowing the acquisition of consecutive measures of angles and angular velocities with a time interval smaller than 10 ms in some cases. Using this routine and other simulator control and monitoring softwares we estimated the angular velocity faster (100 ms × 210 ms)and better than the simulator Rate Readout Module, and used it in a fast real time control simulation.

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.

The increasing development of Unmanned Aerial Vehicle (UAV) technologies has allowed greater use of UAVs as remote sensing platforms to enhance satellite and manned aerial vehicle remote sensing surveillance and environmental management systems. Particularly, the Brazilian National Institute for Space Research - INPE has an Environmental Data Collection System (SCD) since 1993. Recently, the MCTI (Ministry of Science, Technology and Innovation) opened the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN). Both may need additional resources for their expansions in the near future as offered by UAV technologies. These needs illustrate the potential of UAV technologies as complement to existing or future systems. This paper presents an overview of data transmission used in UAVs for remote sensing surveillance and environmental management systems.

Control systems that can switch between control modes have the advantage of being simpler to design than an equivalent system with a single mode. However, the transition between control modes can introduce steps or overshootings in the state variables, and this can degrade the performance or even damage the system. In this work, we will use integral criteria in an original way, 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, using as models the system of control of attitude of the Multimission Platform, and a system which keeps the synchrony between two induction motors.

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.

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.