Investigation of induction motor parameter identification using particle swarm optimization-based RBF neural network (PSO-RBFNN)

High dynamic performance of induction motor drives is required for accurate system information. From the actual parameters, it is possible to design high performance induction motor drive controllers. In this paper, improving the induction motor performance using intelligent parameter identification was proposed. First, machine model parameters were presented by a set of time-varying differential equations. Second, estimation of each parameter was achieved by minimizing the experimental response based on matching of the stator current, voltage and rotor speed. Finally, simulation results demonstrate the effectiveness of the proposed method and great improvement of induction motor performance.   Key words: Induction motor, particle swarm optimization (PSO), parameter identification, least square algorithm.

[1]  Q. H. Wu,et al.  Effective Identification of FOC Induction Motor Parameters Based on Few Measurements , 2002, IEEE Power Engineering Review.

[2]  Guillermo O. Garcia,et al.  Automatic induction machine parameters measurement using standstill frequency-domain tests , 2007 .

[3]  Seung-Ki Sul,et al.  Induction machine parameter identification using PWM inverter at standstill , 1997 .

[4]  Giuseppe Buja,et al.  Self-commissioning of RFO IM drives: one-test identification of the magnetization characteristic of the motor , 2001 .

[5]  Francesco Alonge,et al.  Parameter identification of induction motor model using genetic algorithms , 1998 .

[6]  J. S. Edmonds,et al.  Derivation of Induction Motor Models from Standstill Frequency Response Tests , 1989, IEEE Power Engineering Review.

[7]  Bimal K. Bose,et al.  Power Electronics and Ac Drives , 1986 .

[8]  Mauro Birattari,et al.  Swarm Intelligence , 2012, Lecture Notes in Computer Science.

[9]  Ahmed El-Shafie,et al.  Modified particle swarm optimization for probabilistic slope stability analysis , 2010 .

[10]  Lassaad Sbita,et al.  A robust nonlinear observer for states and parameters estimation and on-line adaptation of rotor time constant in sensorless induction motor drives , 2007 .

[11]  Shantaram S. Pai,et al.  Precision of Sensitivity in the Design Optimization of Indeterminate Structures , 2006 .

[12]  Giuseppe Guidi,et al.  Consideration about problems and solutions of speed estimation method and parameter tuning for speed sensorless vector control of induction motor drives , 2000, Conference Record of the 2000 IEEE Industry Applications Conference. Thirty-Fifth IAS Annual Meeting and World Conference on Industrial Applications of Electrical Energy (Cat. No.00CH37129).

[13]  Paolo Castaldi,et al.  Parameter estimation of induction motor at standstill with magnetic flux monitoring , 2005, IEEE Transactions on Control Systems Technology.

[14]  C. Picardi,et al.  Parameter identification of induction motor based on particle swarm optimization , 2006, International Symposium on Power Electronics, Electrical Drives, Automation and Motion, 2006. SPEEDAM 2006..

[15]  Seung-Ki Sul,et al.  Automatic commissioning for vector controlled AC motors using Walsh functions , 1999, Conference Record of the 1999 IEEE Industry Applications Conference. Thirty-Forth IAS Annual Meeting (Cat. No.99CH36370).

[17]  Amin Mahmoudi,et al.  Improvement of direct torque control in high power induction motors , 2011 .

[18]  Young-Su Kwon,et al.  Standstill Parameter Identification of Vector-Controlled Induction Motors Using the Frequency Characteristics of Rotor Bars , 2009, IEEE Transactions on Industry Applications.

[19]  Mahmudur Rahman,et al.  Particle swarm optimisation prediction model for surface roughness , 2011 .

[20]  A. Keyhani,et al.  Estimation of induction machine parameters from standstill time domain data , 1993, Conference Record of the 1993 IEEE Industry Applications Conference Twenty-Eighth IAS Annual Meeting.

[21]  Cursino B. Jacobina,et al.  The influence of the slip and the speed in the parameter estimation of induction machines , 1997, PESC97. Record 28th Annual IEEE Power Electronics Specialists Conference. Formerly Power Conditioning Specialists Conference 1970-71. Power Processing and Electronic Specialists Conference 1972.

[22]  P. Vadstrup,et al.  Parameter identification of induction motors using differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[23]  Hao Xu,et al.  An improved genetic algorithm for solving simulation optimization problems , 2011 .