Smart torque control for overloaded motor using artificial intelligence approach
This project report presents a methodology for implementation of a rule-based fuzzy logic controller applied to an induction motor torque control. The designed Fuzzy Logic Controller’s performance is weighed against with that of a PI controller. The pros of the Fuzzy Logic Controllers (FLCs) o...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/1915/1/24p%20HAZIZUL%20MOHAMED.pdf http://eprints.uthm.edu.my/1915/2/HAZIZUL%20MOHAMED%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/1915/3/HAZIZUL%20MOHAMED%20WATERMARK.pdf |
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| Summary: | This project report presents a methodology for implementation of a rule-based fuzzy
logic controller applied to an induction motor torque control. The designed Fuzzy
Logic Controller’s performance is weighed against with that of a PI controller. The
pros of the Fuzzy Logic Controllers (FLCs) over the conventional controllers are
they are economically advantageous to develop, a wider range of operating
conditions can be covered using FLCs, and they are easier to adapt in terms of
natural language. Another advantage is that, an initial approximate set of fuzzy rules
can be impulsively refined by a self-organizing fuzzy controller. For torque control
of the induction motor, a reference torque has been used and the control architecture
includes some rules. These rules portray a nonchalant relationship between two
inputs and an output, all of which are nothing but normalized voltages. These are the
input torque error denoted by Error (e), the input derivative of torque error denoted
by Change of error (Δe), and the output frequency denoted by Change of Control
(ωsl). The errors are evaluated according to the rules in accordance to the defined
member functions. The member functions and the rules have been defined using the
FIS editor given in MATLAB. Based on the rules the surface view of the control has
been recorded. The system has been simulated in MATLAB/SIMULINK® and the
results have been attached. The results obtained by using a conventional PI
controller and the designed Fuzzy Logic Controller has been studied and compared. |
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