Robust Input-Output Decoupling Control for Induction Motors with Improved Stator Flux Estimator

Author

Datta, Manoj ; Rafiq, Md Abdur ; Ghosh, B.C.

Author_Institution

Dept. of Electr. & Electron. Eng., Khulna Univ. of Eng. & Technol.

fYear

2006

fDate

19-21 Dec. 2006

Firstpage

362

Lastpage

365

Abstract

A robust input-output decoupling control strategy via non-linear state feedback for stator flux and torque of induction motors (IM) is proposed. To achieve decoupling control, it is shown that the tracking dynamics with respect to the outputs (stator flux amplitude and electrical torque) is asymptotically stable at an admissible operating equilibrium. A real time recurrent learning (RTRL) algorithm based recurrent neural network (RNN) is employed for efficient stator flux measurement. Finally, simulation results are presented to reveal the practicality of the proposed controller

Keywords

asymptotic stability; induction motors; nonlinear control systems; recurrent neural nets; robust control; state feedback; stators; torque control; asymptotic stability; electrical torque; improved stator flux estimator; induction motors; nonlinear state feedback; recurrent learning algorithm; recurrent neural network; robust input-output decoupling control; stator flux measurement; tracking dynamics; Electric variables measurement; Induction motors; Linear feedback control systems; Recurrent neural networks; Robust control; State feedback; Stators; Tellurium; Torque control; Torque measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Computer Engineering, 2006. ICECE '06. International Conference on

Conference_Location

Dhaka

Print_ISBN

98432-3814-1

Type

conf

DOI

10.1109/ICECE.2006.355646

Filename

4178482