| EPSRC Reference: |
GR/J80443/01 |
| Title: |
NEURAL NETWORKS USED FOR SWITCHED RELUCTANCE MOTOR TORQUE RIPPLE REDUCATION |
| Principal Investigator: |
Reay, Professor D |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Computing & Electrical Engineering |
| Organisation: |
Heriot-Watt University |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 April 1994 |
Ends: |
30 September 1997 |
Value (£): |
114,250
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| EPSRC Research Topic Classifications: |
| Electric Motor & Drive Systems |
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Summary on Grant Application Form |
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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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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.hw.ac.uk |