Adaptive Parameter Identification of Sinusoidal Signals

2013 ◽  
Vol 46 (20) ◽  
pp. 624-629
Author(s):  
Jing Na ◽  
Juan Yang ◽  
Xing Wu ◽  
Yu Guo
Keyword(s):  
Parameter Identification ◽  
Adaptive Parameter ◽  
Sinusoidal Signals

scholarly journals Fault Prognosis for Power Electronics Systems Using Adaptive Parameter Identification

2017 ◽  
Vol 53 (3) ◽  
pp. 2862-2870 ◽  
Author(s):  
Jason Poon ◽  
Palak Jain ◽  
Costas Spanos ◽  
Sanjib Kumar Panda ◽  
Seth R. Sanders
Keyword(s):  
Parameter Identification ◽  
Power Electronics ◽  
Adaptive Parameter ◽  
Fault Prognosis

An improved lion swarm optimization for parameters identification of photovoltaic cell models

2019 ◽  
Vol 42 (6) ◽  
pp. 1191-1203
Author(s):  
Zhong-qiang Wu ◽  
Zong-kui Xie ◽  
Chong-yang Liu
Keyword(s):  
Parameter Identification ◽  
Cell Model ◽  
Chaotic Map ◽  
Photovoltaic Cell ◽  
Standard Test ◽  
Local Optimum ◽  
Intelligent Algorithm ◽  
Swarm Optimization ◽  
Test Function ◽  
Adaptive Parameter

In this paper, a parameter identification method of photovoltaic cell model based on improved lion swarm optimization is presented. Lion swarm optimization is a novel intelligent algorithm proposed in recent years, but it has problems such as local optimum and slow convergence. To overcome such limitations, we can combine the tent chaotic map, adaptive parameter and chaotic search strategy to further improve the search ability of the algorithm and avoid trapping in local optimum. The simulation of standard test function shows that the performance of improved lion swarm algorithm is superior to the other six algorithms. Then the algorithm is applied to the parameter identification of photovoltaic cells under two kinds of models and different irradiance, the simulation results verify the superiority and effectiveness of the improved lion swarm optimization in the application of photovoltaic cell parameter identification.

Robust adaptive parameter estimation of sinusoidal signals

Automatica ◽  
2015 ◽  
Vol 53 ◽  
pp. 376-384 ◽  
Author(s):  
Jing Na ◽  
Juan Yang ◽  
Xing Wu ◽  
Yu Guo
Keyword(s):  
Parameter Estimation ◽  
Adaptive Parameter ◽  
Sinusoidal Signals ◽  
Robust Adaptive

Vector Control of Permanent Magnet Synchronous Motor Based on Parameter Identification Technique

2014 ◽  
Vol 644-650 ◽  
pp. 705-708
Author(s):  
Jian Guang Zhu ◽  
Xiao Chen Wang ◽  
Xiao Dong Hou
Keyword(s):  
Parameter Identification ◽  
Vector Control ◽  
Permanent Magnet ◽  
Real Time ◽  
Permanent Magnet Synchronous Motor ◽  
Synchronous Motor ◽  
The Real ◽  
Adaptive Parameter ◽  
Identification Technique ◽  
Time Accuracy

Real-time accuracy of the permanent magnet synchronous motor (PMSM) parameter directly affects the performance of the servo system. In this paper, the model reference adaptive parameter identification method, the parameters of permanent magnet synchronous motor running as the actual model , the mathematical model derived from the equation of state in the d, q coordinate system as the theoretical model , in order to calculate the real-time stator resistance , inductance and rotor flux value . Thereby increasing the accuracy of the vector control .Using simulink simulation results show that, The system can quickly and accurately calculate the real-time parameters and the applied control.

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