A new brushless synchro with look-up table error compensation

Author(s):  
Mahdi Ghafarzadeh ◽  
Ali Kamali E. ◽  
Aliakbar Damaki Aliabad ◽  
Rezvan Abedini ◽  
Mohammad Amin Tajeddini
Electronics ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 1052 ◽  
Author(s):  
Ji ◽  
Lee

This study proposes a field weakening control method with interpolation error compensation of the look-up table based permanent-magnet synchronous machine (PMSM) method. The look-up table (LUT) based control method has robust control characteristics compared to other control methods that use linear controllers for current reference generation. However, it is impossible to store all current references under all circumstances for torque commands. General LUT based control methods use two input parameters. In order to mitigate the effect of discretely stored data, two-dimensional interpolation is used to linearly interpolate values between discontinuous data. However, because the current trajectories of PMSMs are generally ellipsoidal, an error occurs between the linearly interpolated and controllable current references. This study proposes a method to compensate for this interpolation error using a feedforward controller for rapid compensation. The improvement using the proposed method is verified by experiment and simulation.


2014 ◽  
Vol 898 ◽  
pp. 847-850
Author(s):  
Zhao Ji Zhang

Based on the noise analysis of the photoelectric detection circuit, error compensation aiming at photoelectric detection circuit has been performed by making use of interpolation method, look-up table method, adaptive neuro-fuzzy inference method, and surface fitting method, so as to improve the accuracy of photoelectric detection as well as reducing the system error. In the meanwhile, the error compensation effects of different methods are compared and analyzed. Finally, with the help of the MATLAB software, these effects are simulated using the measured data of photoelectric diode experimental platform as the sample data. The result of the simulation indicates that the adaptive neuro-fuzzy inference method can improve the detection accuracy better and its error compensation effect is also better than that of interpolation method, look-up table method, and surface fitting method, when they are under the same conditions.


2016 ◽  
Vol 9 (5) ◽  
pp. 324 ◽  
Author(s):  
Zain Retas ◽  
Lokman Abdullah ◽  
Syed Najib Syed Salim ◽  
Zamberi Jamaludin ◽  
Nur Amira Anang

2015 ◽  
Vol E98.C (4) ◽  
pp. 377-379
Author(s):  
Jonggyun LIM ◽  
Wonshil KANG ◽  
Kang-Yoon LEE ◽  
Hyunchul KU

Kerntechnik ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. 192-202
Author(s):  
D. K. Chandraker ◽  
P. K. Vijayan ◽  
D. Saha ◽  
R. K. Sinha

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