Induction motor modelling using fuzzy logic
Fuzzy logic has been widely used in many engineering applications since this can overcome the limitations of conventional method of data analysis, modelling and system identification, and control system. The capability of dealing with highly non-linear system modelling that is so complex that requir...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2013
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| Online Access: | http://eprints.uthm.edu.my/6695/1/24p%20MOHD%20NASRI%20HASHIM.pdf http://eprints.uthm.edu.my/6695/2/MOHD%20NASRI%20HASHIM%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6695/3/MOHD%20NASRI%20HASHIM%20WATERMARK.pdf |
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| Summary: | Fuzzy logic has been widely used in many engineering applications since this can overcome the limitations of conventional method of data analysis, modelling and system identification, and control system. The capability of dealing with highly non-linear system modelling that is so complex that require absolute analytical design make these mathematical model architecture more popular in the engineering field. This project is addressed on the modelling of induction motor Auto-Regressive with exogenous input (ARX) model structure using fuzzy logic. In this case fuzzy logic is combined with neural network of said Neuro Fuzzy (ANFIS) is applied and has functioned as estimator of the ARX model parameters. The ARX model of induction motor is estimated from its input output data. Input variable is voltage and output variable is speed. The experimental results show that the best model responses have similarly trend with the motor actual responses, final prediction error is 0.00873, loss function is 0.00807, and fit to working data is 67.22%. It means the model produce from system identification able adopt the motor dynamic and can use for replacing real motor for analysis and control design. |
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