基于NNs-MRAS无速度传感器双馈电机LQR控制

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Abstract Concerning the doubly fed induction motor(DFIM) control system without speed sensor, a speed estimation algorithm based on neural networks and model reference adaptive system (NNs-MRAS) is proposed. Differentiation method is adopted to design the neural networks model, and the good speed estimation of DFIM is obtained by training of the neural networks(NNs) through error back propagation. The linear quadratic regulator(LQR) optimal control algorithm is proposed to control the rotor currents in two-phase rotating coordinate system, and the state feedback gain is also designed in this paper. The proposed controller exhibits advanced features as: the parameters of current loop optimal control, improved dynamic and static performances of the control system. Detailed implementation of control strategies is deduced. The control schemes is verified correctly and validly via experimental results of prototype based upon DSP.

Key words： DFIM Neural networks(NNs) MRAS LQR optimal control

Received: 15 April 2013 Published: 05 August 2014

PACS:	TM346
	TM921

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	Liu Yi
	Tan Guojun
	He Fengyou
	An Qi

Cite this article:

Liu Yi,Tan Guojun,He Fengyou等. LQR Controller for Doubly Fed Induction Motor with Speed Sensorless Control Based on NNs-MRAS Method[J]. Transactions of China Electrotechnical Society, 2014, 29(7): 140-146.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2014/V29/I7/140

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