This paper offer a designed module for buck-boost DC-DC converter, able to solve
unsteady charging voltage problem, due to constant decreasing scale of transformers and
grid or solar panel voltage drop, this module has been designed using fuzzy log
ic in PWM
control and simulated in matlab and all test and its results illustrated the suitable figure.
This paper represents a study of all the major and sub influential
factors that affect the process of placing concrete which has
arbitrary nature and has not been stated clearly before; and the
impact of these factors on the cost of a cubic meter of placed
concrete.
In this paper, we will design a Fuzzy Smith Predictor (FSP),
then we will model, simulate and analyze it using colored Fuzzy Petri
networks, then we will compare it with a conventional proportional
integral controller.
The main objective of this
research is to reduce the delay time
of the wind turbine system and to increase its reliability, in the other
side, to improve the response and stability of the operating point of
the mechanical energy and reduce vibration caused by the delay time
in the system.
In the following study we make a simulation of an independent
photovoltaic system connected to an (ohm
- unit of electrical resistance) load which consists of the following
parts:
(Photovoltaic Module - Converter dc- dc - Control system to
track
ing the maximum power point via MATLAB & Simulink
program)
Taking advantage of equations of Photovoltaic Module we chart
the graph and simulate curves of the Module.
We also simulate the converter –type Cuk- which gives higher or
lower voltage than input voltage but with reversed polarity.
We also make a comparison between the two systems tracking:
the first tracker is a traditional one and the second one is a system
in which it uses a fuzzy logic tracker.
The results of the comparison shows different capacities taking into
consideration the varieties of weather conditions of regular solar
radiation as well as the partial shadow.
Such results showed that fuzzy logic has got more capability to
harmonize with all conditions especially in cases of low solar
radiation and partial shadow.
This research aims to produce a diagnosis system for breast cancer by using Neural
Network depending on Back Propagation algorithm(BPNN) and Adaptive Neuro Fuzzy
Inference System ‘ANFIS’, the both of studies was done using structural features of
b
iopsies in “Wisconson Breast Cancer “data base.
In the end a comparison was made between the two studies of malignant- benign
classification of breast masses of breast cancer which has accuracy 95,95% with BPNN
and 91.9% with ANFIS system, this results can be consider very important if they
compared with researches depending on image features that obtained of various devises
like mammography, magnetic resonance.
The fluctuation of voltage cannot be tolerant for equipment in modern industrial
plants such as lighting loads, PLC, robots, and another equipment, which exist in
transmission and distribution systems, so we should use proper aids to regulate volta
ge and
control it.
In this study a (± 25Mvar) Static Synchronous Compensator (STATCOM) is used to
enhance voltage stability in a (66 kv, 1500MV.A) power transmission network. The
STATCOM in this study regulates the voltage of the transmission network for changing in
voltage (± 7%) from the nominal value. A model of the power transmission system and
another model of the STATCOM device, which will enhance the stability of voltage are
designed in MATLAB/Simulink. And the control of (STATCOM) is achieved by using a
Proportional Integrative (PI) controller with Fuzzy Logic Supervisor to adjust the
parameters in PI controller in DC voltage regulator during transient states of load changing
which gives more stability in DC voltage. The results of the simulation are shown. This
study demonstrates the ability of STATCOM for regulating the voltage of the transmission
system by injecting and absorbing reactive power from the power system, and the DC
voltage be more stability by using Fuzzy Logic supervisor.
This paper presents the proposed Method for designing fuzzy
supervisory controller model for Proportional Integral Differential
controller (PID) by Fuzzy Reasoning Petri Net (FRPN),the Features
of Method shows the fuzzification value for each prop
erty of
membership function for each input of fuzzy supervisory controller,
and determine the total number of rules required in designing the
controller before enter the appropriate rules in the design phase of
the rules, and determine the value of the inputs of the rule that has
been activated, and assembly variables that have the same property
and show the value for each of them programmatically, and
determine the deffuzification value using deffuzification methods.
This work seeks to enhance the quality of the educational process output through ensure the quality of its inputs.
This research
aims to develop overlay functions methodology based on fuzzy
logic, reclassify the objects into fuzzy classes, and study the
usability of this method to integrate data of specific phenomenon
to help make optimal decisions.
An ANFIS controller also designed and a comparison
between proposed controller, ANFIS controller and open loop model
had made with different types of disturbance.
