Search Results

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 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

Currently, the use of Global Navigation Satellite Systems-GNSS has been widely disseminated for the most different applications, from the aeronautical navigation to the car traffic, being the Global Positioning System-GPS the most used system for such objectives. New applications have presented challenges in terms of the main requirements associated to such systems, namely: precision, reliability, availability, continuity and integrity. It is because proposed solutions, such as satellite or ground-based augmentation systems, depend on signals provided by the GNSS satellite constellation. It constitutes a limitation for using such systems for position and velocity estimations. On other hand, Inertial Navigation Systems-INS, being independent of external signals, have a big potential to be applied on these circumstances; furthermore, they present characteristics that may be considered complementary to the GNSS.

Currently, the use of Global Navigation Satellite Systems-GNSS has been widely disseminated for the most different applications, from the aeronautical navigation to the car traffic system, being the Global Positioning System-GPS the most used system for such objectives. New applications of such systems have presented more demanding requirements in terms of precision for the position and velocity provided by these systems. Some solutions, as the precision augmentation systems based on satellite or ground improve the precision of the position and velocity estimates. However, the sampling rate of these systems is not substantially improved. Therefore, it constitutes a major limitation of such systems for the position and velocity estimates during high acceleration transients. On other hand, Inertial Navigation Systems- INSs present superior performance under these circumstances.

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.

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.