Approaches to task solution of complex objects identification as example of an induction motor

Mubarakzyanov N.R.E-mail: nail-93@mail.ruScientific adviser: Andrievskaya N.V.

Objective

•To develop parameters estimation method of induction motor.

2

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

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

4

Application area

•complex object identification and control system;

•nonlinear system identification; •multivariable systems identification;• identification of adaptive control system;•nonstationary system identification.

5

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

Identification of induction motor parameters

•Ohmic resistance;•Windings leakage inductance;•Magnetizing inductance between

windings.

7

Identification software

•Fuzzy Logic Toolbox; •Neural Network Toolbox.

8

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

Thank you for your attention!

10