Abstract A standard solution regarding business process management automation in enterprises is the use of workflow management systems working by the Rule-Based Reasoning approach. In such systems, the process model which is designed entirely before the implementation has to meet all needs deriving from business activity of the organization. In practice, it means that great limitations arise in process control abilities, especially in the dynamic business environment. Therefore, new kinds of workflow systems may help which typically work in more agile way e.g. following the Case-Based Reasoning approach. The paper shows another possible solution – the use of emergence theory which indicates among other conditions required to fulfill stimulation of the system (for example the business environment) to run grass-roots processes that lead to arising of new more sophisticated organizing forms. The paper also points the using opportunity of such techniques as the processing of complex events to fulfill key conditions pointed by the emergence theory.

The aim of this paper is presentation and comparison of calculation methods of the inductance matrix of a 3-column multi-winding autotransformer. Main and leakage autotransformer inductance was obtained using finite elements method. Static calculations were made at the current supply for 2D and 3D models, and mono-harmonic calculations were made at the voltage supply. In the mono-harmonic calculations the eddy current losses were taken into account, this made it possible to study relationship between the autotransformer parameters and the frequency. Calculations were made using Ansys and the authors' own programs in Matlab.

The 15-winding and 3-column autotransformer supplying an 18-pulse rectifier circuit was developed. Presented methods can be used also for the autotransformers of other topologies supplying different kinds of converters. Presented methods make it possible to exactly calculate main and leakage inductances of the multi-winding autotransformer. The presented analysis of the eigenvalues and eigenvectors of the inductance matrix makes it possible to identify the influence nature of individual modes on the inductance matrix, and to compare the calculation results obtained using the presented methods. Frequency dependence of autotransformer parameters was shown. Also modes of the impedance matrix of the multi-winding autotransformer was investigated, this made it possible to identify the influence nature of individual modes on the inductance matrix. Using presented methods one can exactly calculate main and leakage inductances of the autotransformer. Thanks to this, one can design in optimal way autotransformers for supplying, for example, rectifier circuits, THD coefficients. The results of the measurements and simulations were also shortly presented at the end of the article.

The paper discusses in detail the construction of the Core Less Axial Flux Permanent Magnet generator simulation model. The model has been prepared in such a way that full compatibility with the elements of the SimPowerSystem library of the Matlab/Simulink package is preserved, which allows easy use of the presented simulation model for testing the work of the generator as part of a larger system. The parameters used in the model come from the MES 3D calculations performed in the Ansys/Maxwell software, for a machine prototype with a rated power of 2.8 kW, which was then used to experimentally verify the correct operation of the presented model of machine.

In this paper a system of a grid side and a generator side converters, both working with a common capacitor, is presented. The 6-phase asymmetric inset-type SMPMSM generator is used. A large pole pair number of this generator enables a gearless wind turbine operation. The fundamental and 3rd harmonic cooperation is used to increase the generator performance. This is accomplished by means of the 3rd harmonic current injection. For that reason the generator side converter must have a neutral connection.

Optimization of industrial processes such as manufacturing or processing of specific materials is a point of interest for many researchers, and its application can lead not only to speeding up the processes in question, but also to reducing the energy cost incurred during them. This article presents a novel approach to optimizing the spindle motion of a computer numeric control (CNC) machine. The proposed solution is to use deep learning with reinforcement to map the performance of the Reference Points Realization Optimization (RPRO) algorithm used in industry. A detailed study was conducted to see how well the proposed method performs the targeted task. In addition, the influence of a number of different factors and hyperparameters of the learning process on the performance of the trained agent was investigated. The proposed solution achieved very good results, not only satisfactorily replicating the performance of the benchmark algorithm, but also, speeding up the machining process and providing significantly higher accuracy.

The development of electric vehicles (EV) necessitates the search for new solutions for configuring powertrain systems to increase reliability and efficiency. The modularity of power supplies, converters, and electrical machines is one such solution. Among modular electric machines, dual three-phase (DTP) motors are the most common in high-power drives. To simplify low and medium power drives for EVs based on DTP PM motor, it is proposed to use a BLDC drive and machine of the simplest design – with concentrated windings and surface mounted PMs on the rotor. To study and create such drives, an improved mathematical model of DTP PM machine was developed in this work. It is based on the results of 2D FEM modeling of the magnetic field. According to the developed method, the dependences of the self and mutual inductances between all phase windings from the angle of rotor position and loads of different motor modulus were determined. Based on these inductances, the circuit computer model of DTP PM machine was created in the Matlab/Simulink. It has a high simulation speed and a high level of adequacy, which is confirmed by experimental studies with a mock-up sample of the electric drive system.

The article presents the algorithm that enables adaptive determination of the amplification coefficient in the filter equation provided by Kalman. The method makes use of an estimation error, which was defined for this purpose, and its derivative to determine the direction of correction changes of the gain vector. This eliminates the necessity to solve Riccati equation, which causes reduction of the method computational complexity. The experimental studies carried out using the proposed approach relate to the estimation of state coordinates describing river pollution using the BOD (biochemical oxygen demand) and DO (dissolved oxygen) indicators).The acquired results indicate that the suggested method does better estimations than the Kalman filter. Two indicators were used to measure the quality of estimates: the Root Mean Squared Error (RMSE) and the Mean Percentage Error (MPE).

The paper presents an off-line application that determines the maximum accuracy of the reference points for the given dynamics parameters of a CNC machine. These parameters are maximum speed, acceleration, and JERK. The JERK parameter determines the rate of change of acceleration. These parameters are defined for each working axis of the machine. The main achievement of the algorithm proposed in the article is the determination of the smallest error specified for each reference point resulting from the implemented G-code for the considered dynamic parameters of the CNC machine. The solutions to this problem in industry consider the improvement in the accuracy of hitting the reference points, but they do not provide information on whether the obtained solution is optimal for such parameters of the machine dynamics. The algorithm makes the accuracy dependent on the adopted dynamic parameters of the machine and the parameters of the PLC controller used in the CNC machine.

This article concerns the use of an integrated RFID system with a mobile robot for the navigation and mapping of closed spaces. The architecture of a prototype mobile robot equipped with a set of RFID readers that performs the mapping functions is described. Laboratory tests of the robot have been carried out using a test stand equipped with a grid of appropriately programmed RFID transponders. A simulation model of the effectiveness of transponder reading by the robot has been prepared. The conclusions from measurements and tests are discussed, and methods for improving the solution are proposed.