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Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

Gutierrez-Villalobos JM, Rodriguez-Resendiz J, Rivas-Araiza EA, Martínez-Hernández MA - Sensors (Basel) (2015)

Bottom Line: These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes.The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime.Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

View Article: PubMed Central - PubMed

Affiliation: Laboratorio de Mecatrónica, Universidad Autónoma de Querétaro, Cerro de las Campanas, Col. Las Campanas, S/N, Queretaro 76010, Mexico. marcelino.gutierrez@uaq.mx.

ABSTRACT
Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

No MeSH data available.


Artificial neural network (ANN) CMAC model.
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sensors-15-15311-f003: Artificial neural network (ANN) CMAC model.

Mentions: The CMAC structure was developed (such as, the human cerebellum), and it is a convenient learning structure for on-line and real-time modeling and controlling induction motors, IMs are non-linear systems. CMAC is capable of learning non-linear functions; it can be defined as a look-up-table. In this structure, each state variable is quantized and mapped, see Figure 3. The space vector is divided into discrete states. The output of each state can be obtained from the sum of the information stored in the associate memories.


Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

Gutierrez-Villalobos JM, Rodriguez-Resendiz J, Rivas-Araiza EA, Martínez-Hernández MA - Sensors (Basel) (2015)

Artificial neural network (ANN) CMAC model.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4541832&req=5

sensors-15-15311-f003: Artificial neural network (ANN) CMAC model.
Mentions: The CMAC structure was developed (such as, the human cerebellum), and it is a convenient learning structure for on-line and real-time modeling and controlling induction motors, IMs are non-linear systems. CMAC is capable of learning non-linear functions; it can be defined as a look-up-table. In this structure, each state variable is quantized and mapped, see Figure 3. The space vector is divided into discrete states. The output of each state can be obtained from the sum of the information stored in the associate memories.

Bottom Line: These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes.The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime.Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

View Article: PubMed Central - PubMed

Affiliation: Laboratorio de Mecatrónica, Universidad Autónoma de Querétaro, Cerro de las Campanas, Col. Las Campanas, S/N, Queretaro 76010, Mexico. marcelino.gutierrez@uaq.mx.

ABSTRACT
Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

No MeSH data available.