Analysis and Design of 5.2GHz Rectangular U Slot Micro strip Patch Antenna Using ANFIS by Harleen Kaur,ECE
Abstract
ANFIS is a network
structure that has learning capability like Neural Networks and
decision making capability like Fuzzy Inference System. ANFIS can be
performed the same as a predictor, estimator or as a controller in a
variety of fields such as time series prediction, pattern recognition
and control system etc.
ANFIS was first
proposed by Jang (1993). In traditional ANFIS, parameters are trained
using the hybrid learning and back propagation alone. At the very
first ANFIS is implemented by Guney(2006) for the computation of
physical dimensions of Rectangular Microstrip patch Antenna.
In the proposed
work, firstly the ANFIS model has to be designed for the frequency
range of 3 - 6.30 GHz. Then the trained ANFIS model is used to design
of rectangular U slot microstrip patch antenna. Afterwards the ANFIS
model will be checked and verified for the estimation of physical
parameters of rectangular U slot microstrip patch antenna such as the
length and width of the rectangular patch, the length and width of
the U slot with reference to IE3D model. The average absolute error
using the proposed method for resonant frequency is 0.5%. The results
show that proposed method produces results which are in excellent
agreement with the simulated data from IE3D software.
This demonstrates
that ANFIS being fast and accurate design methodology can be
implemented to effectively design microstrip patch antennas with
complex structure along with the other related work. Also the
analysis of rectangular U slot antenna is to be done by varying the U
slot position and Feed point. Then the effect of U slot position and
feed point on various antenna output parameters is to be analyzed.
