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cation,
(b) Fuzzy inference and knowledge base, and
(c) Defuzzi
(a) Fuzzi
cation.
Although, a 4-rule FLC require minimum computational memory but suffers
with large deviation in control action from 49-rule FLC, as shown in Fig.
17
. The
proposed approximated FLC overcomes this drawback as shown in Fig.
18
.In
proposed approximated FLC, some additional memory is required than a 4-rule
FLC, to perform approximation using compensating polynomial. Even after this
additional requirement, total memory requirement is much lesser than a 49-rule
FLC.
5 Conclusions
The aim of this chapter is to investigate and analyze the performance of an FLC
with different MFs. Out of the four membership functions used for analysis, the
Gaussian MFs based FLC outperforms others in terms of better dynamic response
in tracking the reference voltage, and effective harmonic compensation in source
current. The harmonic compensation is maintained well within the limits imposed
by IEEE-519 standards.
Hence, Gaussian MFs based FLC is recommended as an optimized FLC con-
firming better performance throughout transient and steady-state conditions and
also justifying its robustness in terms of performance indices depicting minimum
error in regulating the dc-link voltage.
Then, a stepwise design procedure of approximation techniques focused on rule
base size reduction, without compromising the control performance, is discussed.
The Main features of design approach used in approximation technique are:
1. Use of simplest possible FLC
2. Reduced rule base size
3. Process independent design
4. Less memory requirement
5. Less computational efforts
6. Reduced computational time, and
7. Faster response
The performance of designed approximation techniques is validated through
simulation results. The dynamic performance of performance of approximated FLC
is found comparable with the 49-rule FLC and harmonic compensation is even
better at the instants of load perturbation due to smooth transition in entire range of
UOD.
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