In this article is revealed the systems of a good delivery witch implement unmanned aerial vehicles during providing the service. the one channel systems of a goods delivery are a goal of this research work. the close analysing of their functional features, the classification, the types and parameters of different systems from this band are presented. in addition, the modelling of the different types of the one channel systems of goods delivery are has done.
The paper presents the results of biomass estimates of commercial fishes in the South Georgia region made by "swept area" method on the basis of catch statistics of a B-22 Polish trawler in the 1980/1981 season. Total biomass was estimated on about 11 x 104 t.
Maximum score estimation is a class of semiparametric methods for the coefficients of regression models. Estimates are obtained by the maximization of the special function, called the score. In case of binary regression models it is the fraction of correctly classified observations. The aim of this article is to propose a modification to the score function. The modification allows to obtain smaller variances of estimators than the standard maximum score method without impacting other properties like consistency. The study consists of extensive Monte Carlo experiments.
This paper presents maximum score type estimators for linear, binomial, tobit and truncated regression models. These estimators estimate the normalized vector of slopes and do not provide the estimator of intercept, although it may appear in the model. Strong consistency is proved. In addition, in the case of truncated and tobit regression models, maximum score estimators allow restriction of the sample in order to make ordinary least squares method consistent.
The pathological states of biological tissue are often resulted in attenuation changes. Thus, information about attenuating properties of tissue is valuable for the physician and could be useful in ultrasonic diagnosis. We are currently developing a technique for parametric imaging of attenuation and we intend to apply it for in vivo characterization of tissue. The attenuation estimation method based on the echoes mean frequency changes due to tissue attenuation dispersion, is presented. The Doppler IQ technique was adopted to estimate the mean frequency directly from the raw RF data. The Singular Spectrum Analysis technique was used for the extraction of mean frequency trends. These trends were converted into attenuation distribution and finally the parametric images were computed. In order to reduce variation of attenuation estimates the spatial compounding method was applied. Operation and accuracy of attenuation extracting procedure was verified by calculating the attenuation coefficient distribution using the data from the tissue phantom (DFS, Denmark) with uniform echogenicity while attenuation coefficient underwent variation.
The fixed-point theorem is widely used in different engineering applications. The present paper focuses on its applications in optimisation. A Matlab toolbox, chich implements the branch-and-bound optimisation method based on the fixed-point theorem, is used for solving different real-life test problems, including estimation of model parameters for the Jiles-Atherton model.
The influence of wrong information about transition and measurement models on estimation quality has been presented in the paper. Two methods of a particle filter, with and without the Population Monte Carlo modification, and also the extended and unscented Kalman filters methods have been compared. A small 5-bus power system has been used in simulations, which have been performed based on one data set, and this data set has been chosen from among 100 different – to draw the most general conclusions. Based on the obtained results it has been found that for the particle filter methods the implementation of the slightly higher standard deviation than the true value, usually increases the estimation quality. For the Kalman filters methods it has been concluded that optimal values of variances are equal to the true values.
Contemporary sensorless AC drives require the use of electromechanical quantities estimation. The skin effect occurring in AC machines with solid secondary or with solid secondary elements causes machines of this type to be represented by equivalent circuits containing distributed elements, which makes the analysis of machine electrodynamic states more complicated and hinders the construction of relatively simple and effective estimators of electromechanical quantities. The variability of rotor parameters is modelled, with a good approximation, by the machine secondary multi-loop equivalent circuit with lumped elements. In this paper the construction procedure of electromechanical state variable estimators basing on this type of equivalent circuit will be presented. The simulation investigations of the created electromechanical quantities estimators, performed for the selected states of solid iron rotor AC machine operation will be shown as well.
In this paper, we propose a new method of measuring the target velocity by estimating the scaling parameter of a chaos-generating system. First, we derive the relation between the target velocity and the scaling parameter of the chaos-generating system. Then a new method for scaling parameter estimation of the chaotic system is proposed by exploiting the chaotic synchronization property. Finally, numerical simulations show the effectiveness of the proposed method in target velocity measurement.
Velocity is one of the main navigation parameters of moving objects. However some systems of position estimation using radio wave measurements cannot provide velocity data due to limitation of their performance. In this paper a velocity measurement method for the DS-CDMA radio navigation system is proposed, which does not require full synchronization of reference stations carrier frequencies. The article presents basics of FDOA (frequency difference of arrival) velocity measurements together with application of this method to an experimental radio navigation system called AEGIR and with some suggestions about the possibility to implement such FDOA measurements in other kinds of asynchronous DS-CDMA radio networks. The main part of this paper present results of performance evaluation of the proposed method, based on laboratory measurements
The paper presents a new method for simultaneous tracking of varying grid impedance and its uncertainty bounds. Impedance tracking consists of two stages. In the first stage, the actual noise estimate is obtained from least squares (LS) residua. In the second stage, the noise covariance matrix is approximated with the use of residual information. Then weighted least squares (WLS) method is applied in order to estimate impedance and background voltage. Finally uncertainty bounds for impedance estimation are computed. The robustness of the method has been verified using simulated signals. The proposed method has been compared to sliding LS. The results have shown, that the method performs much better than the LS for all considered cases, even in the presence of significant background voltage variations.