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Details of Grant 

EPSRC Reference: GR/J80443/01
Title: NEURAL NETWORKS USED FOR SWITCHED RELUCTANCE MOTOR TORQUE RIPPLE REDUCATION
Principal Investigator: Reay, Professor D
Other Investigators:
Williams, Professor B W Green, Prof. T
Researcher Co-Investigators:
Project Partners:
Department: Computing & Electrical Engineering
Organisation: Heriot-Watt University
Scheme: Standard Research (Pre-FEC)
Starts: 01 April 1994 Ends: 30 September 1997 Value (£): 114,250
EPSRC Research Topic Classifications:
Electric Motor & Drive Systems
EPSRC Industrial Sector Classifications:
Electronics
Related Grants:
Panel History:  
Summary on Grant Application Form
Despite their mechanical simplicity, ruggedness and cost advantages, switch reluctance motors have not found widespread application in servo systems. This is due to their non-linear torque production characteristics which give rise to torque pulsation. This proposal concerns the application of neural networks to the problem of learning the current demand profiles necessary to deliver ripple free demanded torque. Initial simulation work based on experimental static torque measurements has demonstrated the potential of this approach. The neural network solutions found by simulation have been implemented successfully using a digital signal processor. This initial work has suggested the following further work - implementation of real-time, on-line learning using a high bandwidth torque sensor, investigation into the application of constraints to the learning mechanism, incorporation of speed measurement, and development of an FPGA neural network implementation.
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Organisation Website: http://www.hw.ac.uk