Title :
Application of associative memory neural networks to the control of a switched reluctance motor
Author :
Reay, D.S. ; Green, T.C. ; Williams, B.W.
Author_Institution :
Dept. of Comput. & Electr. Eng., Heriot-Watt Univ., Edinburgh, UK
Abstract :
The application of an associative memory neural network to the problem of torque ripple minimisation in a switched reluctance motor is presented. Conventional techniques for torque linearisation and decoupling are reviewed, after which the application of neural techniques to the problem is described. An instrumented test rig based around a 4 kW IGBT converter and a four phase switched reluctance motor has been constructed. Results obtained experimentally and by simulation demonstrate the effectiveness of the approach. The neural network has been implemented using both digital signal processor and field programmable gate array technologies
Keywords :
content-addressable storage; linearisation techniques; machine control; neural nets; reluctance motors; torque control; associative memory neural networks; digital signal processor; field programmable gate array; instrumented test rig; switched reluctance motor; torque decoupling; torque linearisation; torque ripple minimisation; Associative memory; Digital signal processors; Field programmable gate arrays; Instruments; Insulated gate bipolar transistors; Neural networks; Reluctance motors; Switching converters; Testing; Torque;
Conference_Titel :
Industrial Electronics, Control, and Instrumentation, 1993. Proceedings of the IECON '93., International Conference on
Conference_Location :
Maui, HI
Print_ISBN :
0-7803-0891-3
DOI :
10.1109/IECON.1993.339081
