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This paper proposed improvement performance from offline towards online neural network scheme for... more This paper proposed improvement performance from offline towards online neural network scheme for speed control of induction motor field oriented control based on load disturbance and parameter variation. The neural network is design as 1-3-1 network structure by feedforward architecture to maintain the speed trajectory specified by reference model. Both offline and online networks were trained by backpropagation algorithm and the updating of weight and bias will be done in the online model. Simulation model were developed for both networks by using MATLAB/Simulink software and the results shows that the performance of online NNIFOC improved rather than offline NNIFOC and robust to load disturbance and parameter variation.
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— This paper shows the conception and simulation of a single-phase shunt active power filter for ... more — This paper shows the conception and simulation of a single-phase shunt active power filter for harmonics and power factor compensation of uncontrolled rectifier with battery load. The objectives of this project are to minimize the harmonic distortion and intensity the power factor of the single-phase system with battery charger load. The design of shunt active power filter is verified using the simulations in Matlab/Simulink. Shunt active harmonic filter was controlled by the neural network method where it applied the proportional and integral method in order to adjust the direct current link voltage and the hysteresis current controller is employed to generate signals for switching the voltage source inverter. The error signal has been compensated using the controllers. The reference filter currents signal is obtained by subtracting the line current with the compensated signal from the controller. This reference current is fed to the hysteresis current controller and compare with the sensed filter currents to obtain the switching signal for active power filter. Simulation results are acquired with the conventional PI controller and ANN controller.
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— A space vector modulation based direct torque Control strategy is suggested and an intelligence... more — A space vector modulation based direct torque Control strategy is suggested and an intelligence controller design based on this strategy is presented. A neural network controller is proposed to replace the conventional PID controllers to improve the drive's performance since the performance of an electric drive really depends on the quality of a speed controller. The neural network controller was trained and realizes for a speed controller. The controller was utilized in the feedback loop of the control system. The control system renditions as well as the online learning technique of the neural network are described in this paper. The comparison with the conventional PID direct torque controller reveal the effectiveness of the proposed scheme by improved the performance of transient response is presented. A simulation model representing the complete neural network based direct torque control scheme of induction motor drive is developed and verified using S-Function Simulink block program.
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This paper proposes a neural network control voltage tracking scheme of a DC-DC Flyback converter... more This paper proposes a neural network control voltage tracking scheme of a DC-DC Flyback converter. In this technique, a back propagation learning algorithm is employed. The controller is designed to improve performance of the Flyback converter during transient and steady state operations. Furthermore, to investigate the effectiveness of the proposed controller, some operations such as starting-up and reference voltage variations are verified. The numerical simulation results show that the proposed controller has a better performance compare to the conventional PI-Controller method.
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The field oriented control theory and space vector pulse width modulation technique make a perman... more The field oriented control theory and space vector pulse width modulation technique make a permanent magnet synchronous motor can achieve the performance as well as a DC motor. However, due to the nonlinearity of the permanent magnet synchronous motor drive characteristics, it is difficult to control by using conventional proportional-integral-derivative controller. By this reason in this paper an online neural network controller for the permanent magnet synchronous motor is proposed. The controller is designed to tracks variations of speed references and also during load disturbance. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-simulink program. The simulation results show that the proposed controller can reduce the overshoot, settling time and rise time. It can be concluded that the performance of the controller is improved.
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This paper proposed improvement performance from offline towards online neural network scheme for... more This paper proposed improvement performance from offline towards online neural network scheme for speed control of induction motor field oriented control based on load disturbance and parameter variation. The neural network is design as 1-3-1 network structure by feedforward architecture to maintain the speed trajectory specified by reference model. Both offline and online networks were trained by backpropagation algorithm and the updating of weight and bias will be done in the online model. Simulation model were developed for both networks by using MATLAB/Simulink software and the results shows that the performance of online NNIFOC improved rather than offline NNIFOC and robust to load disturbance and parameter variation.
Bookmarks Related papers MentionsView impact
— This paper shows the conception and simulation of a single-phase shunt active power filter for ... more — This paper shows the conception and simulation of a single-phase shunt active power filter for harmonics and power factor compensation of uncontrolled rectifier with battery load. The objectives of this project are to minimize the harmonic distortion and intensity the power factor of the single-phase system with battery charger load. The design of shunt active power filter is verified using the simulations in Matlab/Simulink. Shunt active harmonic filter was controlled by the neural network method where it applied the proportional and integral method in order to adjust the direct current link voltage and the hysteresis current controller is employed to generate signals for switching the voltage source inverter. The error signal has been compensated using the controllers. The reference filter currents signal is obtained by subtracting the line current with the compensated signal from the controller. This reference current is fed to the hysteresis current controller and compare with the sensed filter currents to obtain the switching signal for active power filter. Simulation results are acquired with the conventional PI controller and ANN controller.
Bookmarks Related papers MentionsView impact
— A space vector modulation based direct torque Control strategy is suggested and an intelligence... more — A space vector modulation based direct torque Control strategy is suggested and an intelligence controller design based on this strategy is presented. A neural network controller is proposed to replace the conventional PID controllers to improve the drive's performance since the performance of an electric drive really depends on the quality of a speed controller. The neural network controller was trained and realizes for a speed controller. The controller was utilized in the feedback loop of the control system. The control system renditions as well as the online learning technique of the neural network are described in this paper. The comparison with the conventional PID direct torque controller reveal the effectiveness of the proposed scheme by improved the performance of transient response is presented. A simulation model representing the complete neural network based direct torque control scheme of induction motor drive is developed and verified using S-Function Simulink block program.
Bookmarks Related papers MentionsView impact
This paper proposes a neural network control voltage tracking scheme of a DC-DC Flyback converter... more This paper proposes a neural network control voltage tracking scheme of a DC-DC Flyback converter. In this technique, a back propagation learning algorithm is employed. The controller is designed to improve performance of the Flyback converter during transient and steady state operations. Furthermore, to investigate the effectiveness of the proposed controller, some operations such as starting-up and reference voltage variations are verified. The numerical simulation results show that the proposed controller has a better performance compare to the conventional PI-Controller method.
Bookmarks Related papers MentionsView impact
The field oriented control theory and space vector pulse width modulation technique make a perman... more The field oriented control theory and space vector pulse width modulation technique make a permanent magnet synchronous motor can achieve the performance as well as a DC motor. However, due to the nonlinearity of the permanent magnet synchronous motor drive characteristics, it is difficult to control by using conventional proportional-integral-derivative controller. By this reason in this paper an online neural network controller for the permanent magnet synchronous motor is proposed. The controller is designed to tracks variations of speed references and also during load disturbance. The effectiveness of the proposed method is verified by develop simulation model in MATLAB-simulink program. The simulation results show that the proposed controller can reduce the overshoot, settling time and rise time. It can be concluded that the performance of the controller is improved.
Bookmarks Related papers MentionsView impact