Induction machine based flywheel energy storage system

This study introduces a field oriented controlled (FOC) induction machine based flywheel energy storage (FES) system fed from a 20 kHz high frequency (HF) ac link and pulse density modulated (PDM) Converter. The feasibility of FES system is investigated both in software and hardware and is demonstrated successfully in both cases. The investigated system offers a good potential as a temporary energy storage system for various applications from automobile industry to aerospace applications.     

System sensitivity to parametric variations in the problem of lateral motion flight vehicle control

The results of investigation of dynamic system sensitivity to parametric variations in the channel of flight vehicle lateral motion are presented using the notion of infinitesimal transformation. The exact relationships establishing a link between the structure of parameter deviation and that of system phase coordinate deviation are obtained.     

Onboard system for measuring the parameters of wind vector during parking,starting and takeoff-landing modes for helicopter with aerometric and ion-beacon measuring channels

The problem and features of measuring the speed and the direction angle of the wind vector relative to the longitudinal helicopter axis during parking, starting and takeoff-landing modes by onboard means are considered. The construction principles, information processing algorithms and advantages of onboard system for measuring the wind vector parameters based on ion-beacon and aerometric measuring channels, are disclosed.     

An Upper Bound on Detection Probability for Fluctuating Signals

In the theory of signal detectability, the signal-to-noise ratio (SNR), defined as the quotient of the average received signal energy and the spectral density of the white Gaussian noise, is a fundamental parameter. For a signal which is exactly known, or known except for a random phase, this ratio uniquely defines the detection performance which can be achieved with a matched filter receiver. However, when the signal amplitude is a random parameter, the detection performance is changed and must be determined from the probability density function (pdf) of the amplitude. Relative to the case of a constant signal amplitude, such signal amplitude fluctuation usually degrades performance when a high probability of detection (Pd) is required, but improves performance at low values of Pd; the corresponding change in the required SNR is the so-called signal fluctuation loss Lf. Thus, since Lf in some cases represents an improvement in performance for low values of Pd, a question of at least theoretical interest is: how large might this improvement be, when the class of all signal amplitude pdf's is considered. The solution, presented here, results in a lower bound on the signal fluctuation loss Lf as a function of Pd, or equivalently an upper bound on Pd as a function of SNR. The corresponding most favorable pdf was determined using the Lagrange multiplier technique and results of a numerical maximization are included to provide insight into the general properties of the solution.     

Comment on “Inversion of all principal submatrices of amatrix”

The paper by Koc and Chen (1994) includes new formulas for computational complexity, but the method itself is already known and has dubious numerical stability. A poorly conditioned example is shown     

Neural and fuzzy reconstructors for the virtual flight datarecorder

The results are presented of a comparative study evaluating the performance of neural network (NN) and fuzzy logic reconstructors (FLRs) for the development of a virtual flight data recorder (VFDK). Typical flight data recorders (FDRS) on commercial airliners do not record the aircraft control surface deflections. These dynamic parameters are critical in the investigation of an accident or an uncommanded maneuver. The results are shown relative to a VFDR based on a neural network simulator (NNS) along with a neural network reconstructor (NNR) or a FLR The NNS is trained off-line, using available flight data for the particular aircraft, for the purpose of simulating any desired dynamic output recorded in current FDRs. The NNS is then interfaced with the NNR or with the FLR. The output of the two reconstructors are the control surface deflections which minimize a performance index based on the differences between the available data from the FDR and the output from the NNS. The study tested with night data from a B737-300 shows that both schemes, the one with the NNR and the one with the FLR, provide accurate reconstructions of the control surface deflections time histories     

Image texture synthesis-by-analysis using moving-average models

A synthesis-by-analysis model for texture replication or simulation is presented. This model can closely replicate a given textured image or produce another image that although distinct from the original, has the same general visual characteristics and the same first and second-order gray-level statistics as the original image. The texture synthesis algorithm, proposed contains three distinct components: a moving-average (MA) filter, a filter excitation function, and a gray-level histogram. The analysis portion of the texture synthesis algorithm derives the three from a given image. The synthesis portion convolves the MA filter kernel with the excitation function, adds noise, and modifies the histogram of the result. The advantages of this texture model over others include conceptually and computationally simple and robust parameter estimation, inherent stability, parsimony in the number of parameters, and synthesis through convolution. The authors describe a procedure for deriving the correct MA kernel using a signal enhancement algorithm, demonstrate the effectiveness of the model by using it to mimic several diverse textured images, discuss its applicability to the problem of infrared background simulation, and include detailed algorithms for the implementation of the model     

Radio plasma imager simulations and measurements

The Radio Plasma Imager (RPI) will be the first-of-its kind instrument designed to use radio wave sounding techniques to perform repetitive remote sensing measurements of electron number density (N _e) structures and the dynamics of the magnetosphere and plasmasphere. RPI will fly on the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE) mission to be launched early in the year 2000. The design of the RPI is based on recent advances in radio transmitter and receiver design and modern digital processing techniques perfected for ground-based ionospheric sounding over the last two decades. Free-space electromagnetic waves transmitted by the RPI located in the low-density magnetospheric cavity will be reflected at distant plasma cutoffs. The location and characteristics of the plasma at those remote reflection points can then be derived from measurements of the echo amplitude, phase, delay time, frequency, polarization, Doppler shift, and echo direction. The 500 m tip-to-tip X and Y (spin plane) antennas and 20 m Z axis antenna on RPI will be used to measures echoes coming from distances of several R _E. RPI will operate at frequencies between 3 kHz to 3 MHz and will provide quantitative N _e values from 10^–1 to 10⁵ cm^–3. Ray tracing calculations, combined with specific radio imager instrument characteristics, enables simulations of RPI measurements. These simulations have been performed throughout an IMAGE orbit and under different model magnetospheric conditions. They dramatically show that radio sounding can be used quite successfully to measure a wealth of magnetospheric phenomena such as magnetopause boundary motions and plasmapause dynamics. The radio imaging technique will provide a truly exciting opportunity to study global magnetospheric dynamics in a way that was never before possible.