Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.00 vteřin. 
Suitability Assessment of Learning for Heuristic Adaptive Control of Drives
Kerek, Milan ; Krejsa, Jiří (oponent) ; Březina, Tomáš (vedoucí práce)
The bachelor thesis is aimed to explore the possibilities of using artificial neural network in order to controll nonlinear dynamic systems. In addition the document shows the options to combine neural controllers with linear controllers, such as PID regulator, state space regulator with compensation error. Simulation models were designed in environment of Matlab/Simulink. Neural networks were exploit with the help of Neural Network Toolbox-u. Designed regulators were tested on regulating angular velocity of nonlinear system of 2nd order – wound DC motor.
Suitability Assessment of Learning for Heuristic Adaptive Control of Drives
Kerek, Milan ; Krejsa, Jiří (oponent) ; Březina, Tomáš (vedoucí práce)
The bachelor thesis is aimed to explore the possibilities of using artificial neural network in order to controll nonlinear dynamic systems. In addition the document shows the options to combine neural controllers with linear controllers, such as PID regulator, state space regulator with compensation error. Simulation models were designed in environment of Matlab/Simulink. Neural networks were exploit with the help of Neural Network Toolbox-u. Designed regulators were tested on regulating angular velocity of nonlinear system of 2nd order – wound DC motor.

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