In order to overcome drawback of field oriented control (FOC) method, the principle of HFFC is based on set of rules to control speed of a rotor by utilizing fuzzy frequency controller during the accelerate-decelerate stage.
A T S fuzzy model is firstly formed by utilizing fuzzy theorem to amalgamate a set of linearized dynamic equations.
As for short fuzzy rules, we only use fuzzy rules that satisfy both the minimum confidence and support as candidate rules for the multi-objective genetic fuzzy rule selection mechanism.
After, the design of Adaptive Fuzzy Gain Scheduling of Proportional Integral Controller (AFGPI) for WECS is described, where the optimization by Fuzzy rules is utilized online to adjust the parameters of PI controller based on the error and its first derivative.
We can derive the fuzzy output of probability by the fuzzy rules.
Different from black-box methods, fuzzy rule-based models can not only provide good classification results, but also easily be explained and interpreted in human understandable terms by using fuzzy rules.
The membership functions and fuzzy rules of the DRC are set such that by utilizing the same output fuzzy set for all the controllers, dynamic prioritization is achieved between the delay-sensitive and best-effort traffic.
The fuzzy controllers are designed by utilizing the Matlab's Fuzzy Logic Toolbox.
The fuzzy logic controller (FLC) assimilates to imperialistic competition by adjusting the fuzzy rules to avoid possible errors of the worst imperialist action selection strategy.
Further, the inconsistency estimation in sonar measurement has been evaluated and eliminated by fuzzy rules based model.
