A fuzzy learning—Sliding mode controller for direct field-oriented induction machines
H Rehman, R Dhaouadi - Neurocomputing, 2008 - Elsevier
Neurocomputing, 2008•Elsevier
This paper presents a direct field-oriented induction motor drive system with two distinct
features: a sliding mode voltage mode flux observer (SMVMFO) and a fuzzy model reference
learning controller (FMRLC). The speed of the induction motor is regulated using an
FMRLC, which does not require rigorous tuning of the controller's parameters. The rotor flux
estimation for the direct field orientation (DFO) is realized by a newly proposed SMVMFO,
which is insensitive to the stator resistance variation. The complete drive system is shown to …
features: a sliding mode voltage mode flux observer (SMVMFO) and a fuzzy model reference
learning controller (FMRLC). The speed of the induction motor is regulated using an
FMRLC, which does not require rigorous tuning of the controller's parameters. The rotor flux
estimation for the direct field orientation (DFO) is realized by a newly proposed SMVMFO,
which is insensitive to the stator resistance variation. The complete drive system is shown to …
This paper presents a direct field-oriented induction motor drive system with two distinct features: a sliding mode voltage mode flux observer (SMVMFO) and a fuzzy model reference learning controller (FMRLC). The speed of the induction motor is regulated using an FMRLC, which does not require rigorous tuning of the controller's parameters. The rotor flux estimation for the direct field orientation (DFO) is realized by a newly proposed SMVMFO, which is insensitive to the stator resistance variation. The complete drive system is shown to have very good speed tracking performance, accurate flux estimation and field orientation, and high robustness to stator resistance variation, which has been a long-standing problem in the area of motor drives. Extensive simulations are presented for performance evaluation and validation of the proposed control scheme.
Elsevier
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