The paper deals with the comparison of two estimation methods for torsional torque, load speed and disturbance torque reconstruction based on the Luenberger observer and Kalman filter for two-mass drive system. Estimation errors caused by the drive parameter changes were checked and compared. Due to a lack of analytical methods for gain matrices design for such estimators, parameters of both estimators were optimised using the same genetic-gradient algorithm and the same optimisation index. Such procedure has enabled the detailed comparison of results obtained for these two state estimators, based on simulation and experimental tests.

This paper deals with modelling of the linear induction motor (LIM). Linear induction motors fall into the category of special electrical machines in which the electric energy is converted directly into mechanical energy of translatory motion. LIMs are the most popular ones from the group of linear electric motors, which consists also of DC motors, synchronous motors, reluctance motors, stepping motors, oscillating and hybrid motors.
In the paper mathematical model of a tubular LIM is described by a set of differential equations, which are best solved by numerical methods. Knowledge of the system behaviour under different operating conditions is necessary for proper selection of a LIM for an electrical drive system. Both electromagnetic and mechanical steady state and transient characteristics are important. In many cases, general information about how electrical parameters of the drive (including the control circuit, inertia, friction, and stiffness of the system) influence the transients is necessary, and methods of modelling and digital simulation are the most useful. Nowadays, digital simulation is predominant.
In the case of digital simulation, the mathematical model presents a digital system that is programmed on the basis of mathematical equations describing a real tubular linear induction motor. Finally the calculated values are compared with those measured on a real LIM.

Aspect oriented programming is a programming methodology based on separating concerns (aspects) of computation, describing them separately in the form of advices that are applied in clearly selected set of points of a program using pointcut designators. In this paper we will present an approach to the implementation of crosscutting concept of aspect oriented programming using environmental basis of PFL - a process functional programming language. We will concentrate on the advices, defined by pointcut designators with temporal logic operations. We also introduce possible directions in further conceptual solutions based on process functional paradigm.

This paper deals with the selection of fault states that are further assessed in order to work out operability of a power system. The selection of fault states is necessary for large power systems, where assessment of all possible fault states in terms of system operability would be extremely time-consuming because the number of all fault states can be in the case of complex networks very high. Therefore it is needed to reasonably reduce the number of fault states that are to be assessed. Three different approaches are described in this article. Their goal is to find a set of those faults states that are probable enough in real operation conditions. Only such fault states are then assessed in terms of power reliability and power system operability.

This paper describes principle and design of elastomagnetic torque sensor and with it related neural network model. Multilayer feed-forward neural network was used. The parameters of this neural network were changed in wide range. The most suitable solution is presented. Other neural network solutions have not been presented in this paper. The basic measuring apparatus was set and output characteristics at various input supply current were analyzed. The substitute circuit model of the sensor was determinated from measured data set. The substitute functions for output characteristics were stated by linear regression. The statistical model was compared with neural network model and errors were computed.

The subject matter of this paper is connected with determining identification possibilities of partial discharge (PD) forms based on the analysis of frequency runs of the acoustic emission (AE) pulses generated. In the research carried out so far, the descriptors characterizing the AE pulses measured in the frequency domain were determined, and then their usefulness for the identification of basic PD forms was defined. The results presented here refer to the case when two various single-source PDs occur at the same time in oil insulation. This paper will present the results of frequency analysis of AE pulses generated separately in the setups modeling surface and single-source discharges of the multipoint - grounded plane type. Then, for comparison, the results obtained from simultaneous generation of the discharges of both types will be presented. In the Conclusion the results of the comparative analysis of the results obtained will be presented from the angle of determining identification possibilities in the case of generation of single-source PDs of various types.

The paper deals with rotor fault diagnosis problems of the induction motor using different Artificial Intelligence methods like: neural networks, fuzzy-logic and combined neuro-fuzzy methods. Rotor fault detectors based on these methods were developed. All detectors were trained and tested using measurement data of stator current spectra. The digital signal processor was used for practical realisation of AI-based fault detectors. All detectors were tested in off-line as well as on-line operation. The efficiency of developed neural detectors was evaluated.

In this article is presented the capabilities and practical experience with Alternative Transient Program (ATP). ATP is an universal program system for simulation of transient phenomena of electromagnetic as well as electromechanical nature.
In the article presented we simulation of 220 kV transmission network of Eastern Slovakia. The practical outputs of ATP simulation are compared with the other simulation tool - Matlab.

The paper gives a review of algorithms of quantization of the standard videocodecs. On the basis of the results of statistical analysis of videosignals in DCT domain different modifications of linear and nonlinear algorithms of quantization are presented in intraframe and interframe modes of the videocodecs. Finally an evaluation and comparison of their performances by archieved experimental results have been made.

The paper deals with all conceptions, i.e. conceptions given as transition or excitation functions vs. as the factual decomposition with predefined structure, of canonical decomposition, memory modules and their choise and also the part of state at logical object.

The article deals with design and implementation of the parallel computational environment, which is driven by flow of the data. Design is based on the abstract model of the dataflow computer. This computer is developed at the Dapartment of computers and informatics, Faculty of Electrical engeneering and Informatics, Technical University of Košice (DF KPI)[1],[2]. Parallel computational environment presents design of the computational environment, which devlopment is based on the results of the simulation [3]. It modifies abstract design DF KPI to achieve unified workload on the components of the computer and to minimize count of the parallel access to components of the DF KPI. At the end of the document is presented implementation of the proposed design at the computer net environment, which is most achievable environment for parallel computation.