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134 CHAPTER 4 Performance of MPPT Techniques of Photovoltaic Systems

variables assigned to DD for the different combinations of E and DE are based on the
power converter being used and also on the knowledge of the user.
These linguistic variables of input and output membership functions are then
compared with a set of predesigned values during aggregation stage. The relation
between the inputs and output depends on the experience of the system designer.
These relations can be tabulated as shown in Table 4.2 [40]. Some researchers pro-
portionate these variables to only five fuzzy subset functions as in Eltamaly [40].
Table 4.2 can be translated into 49 fuzzy rules (IF-THEN rules) to describe the
knowledge of control. Some of these rules are shown in the following as an example:

R 25 : If E is NM and DE is PS then DD is NS
R 63 : If E is PM and DE is NS then DD is PS
/
/
R 51 : If E is PS and DE is NB then DD is NM
In the defuzzification stage, the FLC output is converted from a linguistic vari-
able to a numerical variable by using membership function. This provides an analog
signal, which is the change in the duty ratio, DD, of the boost converter. This value is
subtracted from previous value of the duty ratio to get its new value as shown in
Eq. (4.14).
Defuzzification is used for converting the fuzzy subset of control form inference
back to values. As the output usually required a nonfuzzy value of control, a defuz-
zification stage is needed. Defuzzification for this system is the height method. The
height method is both very simple and very fast method. The height defuzzification
method is a system of rules formally given by Eq. (4.26):
m
P
cðkÞ W k
k¼1
DD ¼ (4.26)
P n
W K
k¼1
where DD ¼ change of control output; c(k) ¼ peak value of each output;
W k ¼ height of rule k.
The FLC is implemented using the fuzzy logic tool box available in MATLAB/
Simulink. Fuzzy logic toolbox contains a tool called fuzzy inference system (FIS)
editor available with MATLAB/Simulink. The FIS editor is an effective graphical
user interface (GUI) tool provided with the fuzzy logic toolbox in Matlab/Simulink
to simplify the design of the FLC, which can be used in the system under investiga-
tion. The input and output membership functions are designed in the FIS editor.
The relation between the input and output membership functions can be intro-
duced in the aggregation stage. Aggregation stage is carried out in the FIS editor
by introducing the rules of Table 4.2 into FIS editor. The rules that come into
play for different values of inputs and the corresponding outputs can be viewed using