Behavioural Non-Linearties Compensation Using AdvancedFuzzyLogic Model
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The two layer fuzzylogic controller for the performance improvement of synchronous generator has been developed in this work. The two layers contain several membership functions for fuzzification, if-then rules for decision making and defuzzification method used Mamdani model using MATlab. The input data was taken on an experimental setup involving synchronous generator of industrial scale. It has been shown that the two layers provide full range control of the machine. The two layers designed and developed in the model take different control variable so as to offer the control leading to perf...
The two layer fuzzylogic controller for the performance improvement of synchronous generator has been developed in this work. The two layers contain several membership functions for fuzzification, if-then rules for decision making and defuzzification method used Mamdani model using MATlab. The input data was taken on an experimental setup involving synchronous generator of industrial scale. It has been shown that the two layers provide full range control of the machine. The two layers designed and developed in the model take different control variable so as to offer the control leading to performance improvement of machine under various operating conditions. The simulation has been carried out using MATlab. The developed fuzzy logic model can be implemented through various hardware which are commercially available. The only difference in the conventional fuzzy logic control and two layer fuzzy logic .control as proposed and developed in the work is that a selector switch is required (like low range and high range selector switch is to execute different layers of FLC for the different input sub-ranges.
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