NDLI: Online $H_{∞}$ speed control of sensorless induction motors with rotor resistance estimation

Content Provider	IEEE Xplore Digital Library
Author	Medagam, P.V. Pourboghrat, F.
Copyright Year	2007
Description	Author affiliation: Southern Illinois Univ. at Carbondale, Carbondale (Medagam, P.V.)
Abstract	This paper proposes an online technique for the $H_{∞}$ control of speed and flux norm of current-fed induction motors (IM). Integrals of the speed and flux norm tracking errors are considered as elements of the state variables. A robust $H_{∞},$ optimal control strategy for this problem is determined by solving the algebraic Riccati equation (ARE), using multilayer recurrent neural networks. The proposed controller allows for the simultaneous and independent control of both speed and flux norms of the induction motors. The control implementation involves estimating the rotor flux, rotor resistance, and speed of the induction motor, using continuous-time extended Kalman filter (EKF). The simulation results show the effectiveness of the proposed controller even in the presence of rotor resistance and load torque disturbances.
Starting Page	1307
Ending Page	1312
File Size	1154069
Page Count	6
File Format	PDF
ISBN	9781424406449
DOI	10.1109/PEDS.2007.4487873
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-27
Publisher Place	Thailand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Induction motors Rotors Sliding mode control Sensorless control Optimal control Robust control Riccati equations Torque control Stators Control systems Online H_∞ control Induction motor Neural networks Extended Kalman filter Speed and rotor resistance estimation
Content Type	Text
Resource Type	Article

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