Adaptive Sliding-Mode Neuro-Fuzzy Control of the Two-Mass Induction Motor Drive Without Mechanical Sensors

In this paper, the concept of a model reference adaptive control of a sensorless induction motor (IM) drive with elastic joint is proposed. An adaptive speed controller uses fuzzy neural network equipped with an additional option for online tuning of its chosen parameters. A sliding-mode neuro-fuzzy...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2010-02, Vol.57 (2), p.553-564
Main Authors: Orlowska-Kowalska, T., Dybkowski, M., Szabat, K.
Format: Article
Language:English
Subjects:
Adaptive control
Adaptive control systems
Artificial neural networks
Computer simulation
Control systems
elastic coupling
Estimators
Fuzzy control
Fuzzy logic
Fuzzy neural networks
Fuzzy sets
induction motor (IM)
Induction motor drives
Induction motors
Mathematical models
Mechanical sensors
Motors
Neural networks
Programmable control
Sensorless control
Sliding mode control
Studies
Tuning
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Summary:In this paper, the concept of a model reference adaptive control of a sensorless induction motor (IM) drive with elastic joint is proposed. An adaptive speed controller uses fuzzy neural network equipped with an additional option for online tuning of its chosen parameters. A sliding-mode neuro-fuzzy controller is used as the speed controller, whose connective weights are trained online according to the error between the estimated motor speed and the speed given by the reference model. The speed of the vector-controlled IM is estimated using the MRAS CC rotor speed and a flux estimator. Such a control structure is proposed to damp torsional vibrations in a two-mass system in an effective way. It is shown that torsional oscillations can be successfully suppressed in the proposed control structure, using only one basic feedback from the motor speed given by the proposed speed estimator. Simulation results are verified by experimental tests over a wide range of motor speed and drive parameter changes.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2009.2036023