Speed estimator in closed-loop scalar control using neural networks

This work proposes an artificial neural network approach to estimate the induction motor speed applied in a closed-loop scalar control. The induction motor speed is the important quantity in an industrial process. Thus, when the load coupled to the axis needs speed control, some of the drive and control strategies are based on the estimated axis speed of the motor. This paper proposes an alternative methodology for estimating the speed of a three phase induction motor driven by a voltage source inverter, using space vector modulation under the scalar control strategy and based on artificial neural networks. Experimental results are presented to validate the performance of the proposed method under motor load torque and speed reference set point variations.

[1]  Yüksel Oğuz,et al.  Speed estimation of vector controlled squirrel cage asynchronous motor with artificial neural networks , 2011 .

[2]  Alessandro Goedtel,et al.  Embedded DSP-Based Compact Fuzzy System and Its Application for Induction-Motor $V/f$ Speed Control , 2011, IEEE Transactions on Industrial Electronics.

[3]  Humberto Pinheiro,et al.  Space vector modulation for voltage-source inverters: a unified approach , 2002, IEEE 2002 28th Annual Conference of the Industrial Electronics Society. IECON 02.

[4]  Rong-Ching Wu,et al.  Parameter Identification of Induction Machine With a Starting No-Load Low-Voltage Test , 2012, IEEE Transactions on Industrial Electronics.

[5]  B. Jeftenic,et al.  Speed-sensorless control of induction motor based on reactive power with rotor time constant identification , 2010 .

[6]  H. van der Broeck,et al.  Analysis and Realization of a Pulse Width Modulator Based on Voltage Space Vectors , 1986, 1986 Annual Meeting Industry Applications Society.

[7]  Alessandro Goedtel,et al.  Harmonic distortion monitoring for nonlinear loads using neural-network-method , 2013, Appl. Soft Comput..

[8]  L. Parsa,et al.  Model Reference Adaptive Control of Five-Phase IPM Motors Based on Neural Network , 2011, IEEE Transactions on Industrial Electronics.

[9]  Haitham Abu-Rub,et al.  Speed Sensorless Induction Motor Drive With Predictive Current Controller , 2013, IEEE Transactions on Industrial Electronics.

[10]  Mostafa F. Shaaban,et al.  A speed estimation unit for induction motors based on adaptive linear combiner , 2009 .

[11]  S. Kumar,et al.  A critical evaluation and experimental verification of Extended Kalman Filter, Unscented Kalman Filter and Neural State Filter for state estimation of three phase induction motor , 2011, Appl. Soft Comput..

[12]  Leonardo Bruno Garcia Campanhol,et al.  A comparative analysis of p-PLL algorithms for single-phase utility connected systems , 2009, 2009 13th European Conference on Power Electronics and Applications.

[13]  R. Krishnan,et al.  Electric Motor Drives: Modeling, Analysis, and Control , 2001 .

[14]  Ming-Feng Yeh,et al.  Application of CMAC neural network to the control of induction motor drives , 2009, Appl. Soft Comput..

[15]  Veran V. Vasic,et al.  A stator resistance estimation scheme for speed sensorless rotor flux oriented induction motor drives , 2003 .

[16]  Chee-Mun. Ong,et al.  Dynamic simulation of electric machinery : using MATLAB/SIMULINK , 1997 .

[17]  Yassine Koubaa,et al.  Luenberger state observer for speed sensorless ISFOC induction motor drives , 2012 .

[18]  Thomas G. Habetler,et al.  Using PWM-Induced Transient Excitation and Advanced Signal Processing for Zero-Speed Sensorless Control of AC Machines , 2010, IEEE Transactions on Industrial Electronics.

[19]  Chuan-Kai Lin.  Radial basis function neural network-based adaptive critic control of induction motors , 2011, Appl. Soft Comput..

[20]  Damian Giaouris,et al.  Sensorless Control of Induction Motor Drives at Very Low and Zero Speeds Using Neural Network Flux Observers , 2009, IEEE Transactions on Industrial Electronics.

[21]  A. Goedtel,et al.  An ANN strategy applied to induction motor speed estimator in closed-loop scalar control , 2012, 2012 XXth International Conference on Electrical Machines.