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Recurrent wavelet neural network controller with improved particle swarm optimisation for induction generator system

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4 Author(s)
Teng, L.-T. ; Dept. of Electr. Eng., Nat. Dong Hwa Univ., Hualien ; Lin, F.-J. ; Chiang, H.-C. ; Lin, J.-W.

A recurrent wavelet neural network (RWNN) controller with improved particle swarm optimisation (IPSO) is proposed to control a three-phase induction generator (IG) system for stand-alone power application. First, the indirect field-oriented mechanism is implemented for the control of the IG. Then, an AC/DC power converter and a DC/AC power inverter are developed to convert the electric power generated by a three-phase IG from variable frequency and variable voltage to constant frequency and constant voltage. Moreover, two online trained RWNNs using backpropagation learning algorithm are introduced as the regulating controllers for both the DC-link voltage of the AC/DC power converter and the AC line voltage of the DC/AC power inverter. Furthermore, an IPSO is adopted to adjust the learning rates to further improve the online learning capability of the RWNN. Finally, some experimental results are provided to demonstrate the effectiveness of the proposed IG system.

Published in:

Electric Power Applications, IET  (Volume:3 ,  Issue: 2 )

Date of Publication:

March 2009

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