Combining fuzzy Luenberger observer and Kalman filter for speed sensorless integral backstepping controlled induction motor drive

被引：9

作者：

Bennassar A. ^{[1
]}

Abbou A. ^{[1
]}

Akherraz M. ^{[1
]}

机构：

[1] Laboratory of Power Electronics and Control, Department of Electrical Engineering, Mohammed V University in Rabat, Mohammadia School's of Engineers, Street Ibn Sina, Agdal

来源：

International Journal of Automation and Control | 2017年 / 11卷 / 03期

关键词：

Fuzzy adaptation mechanism; Induction motor drives; Integral backstepping control; Kalman filter; Luenberger observer; Lyapunov theory; Sensorless control;

D O I：

10.1504/IJAAC.2017.084871

中图分类号：

学科分类号：

摘要：

In the present work, we propose a new sensorless backstepping control with integral action for three-phase induction motor drives (IM) and with an estimation of the rotor speed and flux. The idea is to use a Luenberger observer with fuzzy adaptation mechanism to estimate the rotor speed, while the rotor flux is estimated by a Kalman filter. The integral backstepping design for direct field oriented control (DFOC) based on Lyapunov theory is a powerful tool to steer the speed variable to its reference and to compensate the uncertainties. A Lyapunov theory is used and demonstrates that the dynamic trajectories tracking are asymptotically stable. Numerical simulation results obtained in MATLAB/Simulink environment are illustrated and show the good dynamic performance of the integral backstepping speed controller and the effectiveness of the proposed new sensorless strategy in different working of speed trajectories and in the presence of the load torque. © Copyright 2017 Inderscience Enterprises Ltd.

引用

页码：298 / 313

页数：15

共 15 条

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[3]

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[10]

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