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Artificial neural networks as models neuronal electronic state offices

Tchórzewski J., Leszko K.

Information Systems in Management

2015

Vol. 4, No. 3

219--227

The paper presents selected results of research on learning design and artificial neural network (ANN) models paperless office as a state defined as a document repository. A review of selected issues on artificial neural network, and environments to support their generation and learning. In particular, attention was drawn to the new modeling capabilities leading to obtaining neural models of electronic systems. Artificial neural network is designed and taught her electronic office model based on the size of the input 11 and 9 variables, par 72 trainees on the actual size of government agencies for the year 2007. The model was obtained in MATLAB and Simulink and using the Neural Network Toolbox. Showing the possibilities of using the model to test sensitivities and simulation in Simulink.

Development of the electrical power system from the point of view of unmanned factories

Tchórzewski J.

Computer Applications in Electrical Engineering

2014

Vol. 12

144--161

Fundamentals of systems and control theory as well as systems development identification theory were used for the purpose of the DPS Identification, which allowed to generate models of development, including models of development in the form of matrix th and the equations in the states space (ss). This served as the basis to develop the systemic model of the DPS system development, which was implemented in Simulink, by defining successive blocks of the model as characteristics of individual subsystems of the DPS, identified in the MATLAB environment using the System Identification Toolbox, and transformed into the models in the state space using the Control System Toolbox. As a result of solving a set of equations of state variables using an m-file in the MATLAB environment three state variables were obtained. Based on the obtained solution, responses of the DPS system (output variable y1) to the following types of input functions: unit step 1(θ), Dirac impulse δ(θ) and sin(θ) function were obtained. The results of experiments were interpreted. An attempt to design a system that corrects and adjusts the functioning of the model of the DPS was made using state regulator and state observer as an example.