1. Approaches to task solution of complex objects identification as example of an induction motor Mubarakzyanov N.R. E-mail: nail-93@mail.runail-93@mail.ru Scientific adviser: Andrievskaya N.V.

2. Objective To develop parameters estimation method of induction motor. 2

3. Problems of classic identification methods impossibility of use under uncertainty conditions; complexity of high-order systems identification, multivariable systems, nonlinear systems, etc; limited operability under conditions of limited measurability. 3

4. Modern methods of identification Fuzzy algorithm; Artificial neural network; Artificial fuzzy neural network. 4

5. Application area complex object identification and control system; nonlinear system identification; multivariable systems identification; identification of adaptive control system; nonstationary system identification. 5

6. Examples of using the modern identification methods Fuzzy neural network identification of synchronous generator parameters ; Nonlinear function identification of inversion; Neural network approach to identification task solution of nonstationary parameters of technological objects; Application of neural recurrence network for parameters identification of dc motor. 6

7. Identification of induction motor parameters Ohmic resistance; Windings leakage inductance; Magnetizing inductance between windings. 7

8. Identification software Fuzzy Logic Toolbox; Neural Network Toolbox. 8

9. Conclusion Research of the induction motor model with a squirrel cage has showed that the induction motor is a nonlinear and non-stationary object and the estimation of its parameters by means of classical methods is rather difficult. 9

10. Thank you for your attention! 10