scholarly journals Optimal dc reference voltage in HVDC grids

2015 ◽  
Author(s):  
R.H. Renner ◽  
J. Beerten ◽  
D. Van Hertem
Keyword(s):  
Reference Voltage

Approximation Piecewise Stabilization of the Thermal Voltage Coefficient of Reference Voltage Sources

2020 ◽  
Vol 91 (7) ◽  
pp. 433-439
Author(s):  
M. A. Mastepanenko ◽  
S. N. Bondar ◽  
Sh. Zh. Gabrielyan ◽  
A. V. Ivashina
Keyword(s):  
Reference Voltage ◽  
Voltage Coefficient ◽  
Thermal Voltage

Neuro Fuzzy Controller for DTC of Induction Motor Using Multilevel Inverter with SVM

2021 ◽  
pp. 2150250
Author(s):  
B. Kiran Kumar ◽  
Y. V. Siva Reddy ◽  
M. Vijaya Kumar
Keyword(s):  
Induction Motor ◽  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Reference Voltage ◽  
Training Dataset ◽  
Testing Time ◽  
Hybrid Technique ◽  
Nonlinear Loads ◽  
Neuro Fuzzy ◽  
Voltage Signal

In this paper, an effective neuro-fuzzy controller (NFC) technique has been proposed to control the induction motor torque and flux. The NFC hybrid technique is the grouping of the neural network (NN) and fuzzy logic controller (FLC), which generated the target voltages with the corresponding input flux and torque. The novelty of the proposed hybrid technique is highly flexible in nonlinear loads, convenient user interface and logical intellectual and permitting for integrated controlling schemes. Here, the FLC generates the training dataset of the NN technique based on the logical rules. The generated dataset contains the information about the flux and torque deviation parameters and the corresponding reference voltage parameters. The NN has been trained based on training dataset and the testing time which produces the optimal reference voltage parameters depends on the variation of the torque and flux parameters. By using the output of the NFC technique, the space vector modulation (SVM) develops the appropriate control pulses to the five-level inverter and the inverter generates the output voltage signal to the induction motor. The proposed method is designed in the MATLAB/Simulink platform and the outputs are verified through the comparison analysis with the existing techniques.

scholarly journals Adaptive Fuzzy PI Current Control of Grid Interact PV Inverter

2018 ◽  
Vol 8 (1) ◽  
pp. 472 ◽  
Author(s):  
R.S. Ravi Sankar ◽  
S.V. Jayaram Kumar ◽  
G. Mohan Rao
Keyword(s):  
Power Generation ◽  
Pulse Width Modulation ◽  
Fuzzy Controller ◽  
Pi Controller ◽  
Current Control ◽  
Reference Voltage ◽  
Voltage Source ◽  
Pv Inverter ◽  
Photo Voltaic ◽  
Pv Power Generation

Now a day‟s, Photo Voltaic (PV) power generation rapidly increasing. This power generation highly depending on the temperature and irradiation. When this power interface with grid through the voltage source inverter with PI controller. Its gains should be updated due to the parametric changes for the better performance. In This Work Fuzzy Controller updates the gains of the proportional integral (PI)s Controller under variable parametric conditions. the gaines of the PI Controller are updated based on the error current and change in error current through the fuzzy controller. The error current in direct and quadrature frame are the Inputs to the PI controller. The PI Controller generates the reference voltage to the pulse width modulation technique. Here reference voltage is compared with the carrier signal to generate the pulses to the 3-Ph Inverter connected to the grid. This controller has given well dynamic response with less steady state error and also given The less THD of the grid current compared to the PI and Fuzzy controller.It Is implemented and verified in MATLAB Simulink.

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