Modeling and control strategy of three phase neutral point clamped multilevel PV inverter connected to the grid

2015 ◽  
Vol 3 ◽  
pp. 195-202 ◽  
Author(s):  
K Arulkumar ◽  
D Vijayakumar ◽  
K Palanisamy
Keyword(s):  
Control Strategy ◽  
Neutral Point ◽  
Modeling And Control ◽  
Pv Inverter ◽  
Three Phase ◽  
And Control

Modeling and Control of a Master–Slave PV Inverter With N-Paralleled Inverters and Three-Phase Three-Limb Inductors

2013 ◽  
Vol 28 (6) ◽  
pp. 2842-2855 ◽  
Author(s):  
M. Borrega ◽  
L. Marroyo ◽  
R. Gonzalez ◽  
J. Balda ◽  
J. L. Agorreta
Keyword(s):  
Modeling And Control ◽  
Pv Inverter ◽  
Three Phase ◽  
And Control

scholarly journals A Switching System oriented Modeling and Control Strategy for Idle Speed Control of a Hybrid Powertrain

2020 ◽  
Vol 53 (2) ◽  
pp. 14028-14033
Author(s):  
Micha S. Obergfell ◽  
Steven X. Ding ◽  
Frank Wobbe ◽  
Christoph-Marian Goletz ◽  
Michael Folkers ◽  
...  
Keyword(s):  
Control Strategy ◽  
Speed Control ◽  
Switching System ◽  
Hybrid Powertrain ◽  
Modeling And Control ◽  
Idle Speed ◽  
Idle Speed Control ◽  
And Control

Biostability in distribution systems in one city in southern China: Characteristics, modeling and control strategy

2014 ◽  
Vol 26 (2) ◽  
pp. 323-331 ◽  
Author(s):  
Pinpin Lu ◽  
Xiaojian Zhang ◽  
Chiqian Zhang ◽  
Zhangbin Niu ◽  
Shuguang Xie ◽  
...  
Keyword(s):  
Control Strategy ◽  
Distribution Systems ◽  
Southern China ◽  
Modeling And Control ◽  
And Control

NEURAL MODELING AND CONTROL OF DYNAMIC SYSTEMS WITH HYSTERESIS

2007 ◽  
Vol 31 (1) ◽  
pp. 127-141
Author(s):  
Yonghong Tan ◽  
Xinlong Zhao
Keyword(s):  
Dynamic Systems ◽  
Control Strategy ◽  
Neural Modeling ◽  
Modeling And Control ◽  
Control Scheme ◽  
The Neural Networks ◽  
Adaptive Control Strategy ◽  
Set Up ◽  
Modeling Strategy ◽  
And Control

A hysteretic operator is proposed to set up an expanded input space so as to transform the multi-valued mapping of hysteresis to a one-to-one mapping so that the neural networks can be applied to model of the behavior of hysteresis. Based on the proposed neural modeling strategy for hysteresis, a pseudo control scheme is developed to handle the control of nonlinear dynamic systems with hysteresis. A neural estimator is constructed to predict the system residual so that it avoids constructing the inverse model of hysteresis. Thus, the control strategy can be used for the case where the output of hysteresis is unmeasurable directly. Then, the corresponding adaptive control strategy is presented. The application of the novel modeling approach to hysteresis in a piezoelectric actuator is illustrated. Then a numerical example of using the proposed control strategy for a nonlinear system with hysteresis is presented.

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