The thesis involved the design, implementation and testing of a second order neuro-fuzzy controller for the speed control of an AC induction motor, and a comparison of the neuro-fuzzy controller's performance with that of the PI algorithm. It was found experimentally, that the operating temperature of the AC induction motor affected the ability of the PI controller to maintain the set speed. The linear PI algorithm approximation was observed to produce transient speed responses when sudden changes in load occurred. The neuro-fuzzy design was found to be quite involved in the initial design stages. However, after the initial design, it was a simple matter of fine-tuning the algorithm, to optimize performance for any parameter variations of the motor due to temperature or due to sudden changes in load. The neuro-fuzzy algorithm can be developed utilising one of two methods. The first method utilises sensor-less control by detailed modeling of the induction motor; where all varying parameters of the motor are modeled mathematically. This involves using differential equations, and representing them in the form of system response block diagrams. When the overall plant transfer function is known, a fuzzy PI algorithm can be utilised to control the processes of the plant. The second method involves modeling the overall output response as a second order system. Raw data can then be generated in a text file format, providing control data according to the modeled second order system. Using the raw data, development software such as FuzzyTECH is utilised to perform supervised learning, so to produce the knowledge base for the overall system. This method was utilised in this thesis and compared to the conventional PI algorithm. The neuro-fuzzy algorithm implemented on a PLC was found to provide better performance than the PI algorithm implemented on the same PLC. It provided also in the added flexibility for further fine-tuning and avoided the need for rigorous mathematical manipulation of linear equations / Master of Engineering (Hons)
| Identifer | oai:union.ndltd.org:ADTP/182179 |
| Date | January 2002 |
| Creators | Khiyo, Sargon, University of Western Sydney, College of Science, Technology and Environment, School of Engineering and Industrial Design |
| Source Sets | Australiasian Digital Theses Program |
| Language | English |
| Detected Language | English |
| Source | THESIS_CSTE_EID_Khiyo_S.xml |
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