This paper presents a strategy of variable speed wind turbine connected to a permanent magnet synchronous generator; the goal is to get the most possible wind turbines. We used a wind energy conversion system model consisting of a wind turbine, perma
nent magnet synchronous generator, rectifier, buck-boost chopper, inverter, load, and traditional controller PI to stabilize the voltage obtained from the wind turbine and synchronous generator at a variable wind speed. Then we used one of the artificial intelligence techniques represented by the genetic algorithm to get the maximum possible wind turbine. The traditional controller PI and the genetic algorithm we modeled using the Matlab R2014a program and from it we obtained the advantages of mechanical power for wind turbine and determined maximum power points at each wind speed.
This research aims to design
an effective system for detection of various known and unknown intrusion and
snooping operations which are SCADA systems exposed to, depending on the
idea of Markov Chains and the concept of probability windows.
In this research a proportional integral differential classic (PID
controller) and state feedback controller was designed to control the in
the inverted pendulum and a comparison between all the cases and
choose the most suitable controller using MATLAB / SIMULINK
program
As known the electric energy is one of the most important factor of development, but
using it causes bad environmental impacts due to depending on fuel as the source of
electrical generation. Using renewable energy is still limited and needs a huge
fixed costs,
so it is important to reduce electrical consumption by monitoring and controlling
equipment to achieve its function with lower consumption. HVAC sector is the most
consumption part in buildings, therefor any saving in this sector will affect manifestly on
the total electrical consumption in the building and this is done by control system. Control
systems are in continuous improving, so it is needed to exploit them in saving electrical
energy.
In this research, studying control of VAV system and designing fuzzy logic
controller to drive supply fan in order to reduce its electrical consumption, this is
performed through designing practical prototype of the supply fan with its tools and
software which are designed to view the electrical energy saving which we gain it by using
fuzzy logic controller.
This research deals with improving the efficiency of solar photovoltaic (PV) power
systems using a Fuzzy Logic Controller (FLC) for Maximum Power Point Tracking
(MPPT), to control the duty cycle of DC-DC Voltage Converter, to achieve the
photovolt
aic system works at a Maximum Power Point under different atmospheric
changes of the solar insolation and ambient temperature. In this context, this research
presents a new model for FLC developed in Matlab/Simulink environment. The proposed
model for the controller is based on the conventional Perturb and Observe (P&O)
technique. Where, in similar to the conventional P&O technique, the changes in the Power
and tension of photovoltaic power system, are considered as the input variables of the
proposed controller, while the output variable is the change in the duty cycle. The main
advantage of the developed controller FLC, based on the considering the change in the
duty cycle has a Variable Step Size, and directly related to the changes in the power and
tension of the Photovoltaic system. Which make it possible to overcome the problem of
fixed Step Size in the change of the duty cycle in the conventional MPPT- P&O Controller
based on P&O technique. The MPPT- P&O Fuzzy, works by a variable step size achieve a
fast speed response and high efficiency for tracking the MPP point under sudden and
rapidly varying atmospheric conditions, compared with the conventional MPPT- P&O. The
simulation results completed in Matlab/Simulink environment, showed the best
performance of developed MPPT- P&O Fuzzy controller in tracking the MPP by achieving
a better dynamic performance and high accuracy, compared with the use of the
conventional MPPT- P&O under different atmospheric changes.
يهدف هذا المشروع إلى تطوير الجزء الخاص بالتحكم العرضي للعربة الذي يهتم
بمنع العربة من الخروج عن المسار عند المنعطفات و سيتم ذلك من خلال بناء
متحكم يعتمد في بنيته على نظرية الشبكات العصبونية العائمة التي تدمج ما بين
التحكم العائم و الشبكات العصبوني
ة، و ستكون مهمته بشكل اساسي تعديل حركة
المقود بحيث تتوافق مع المنعطفات على الطريق الذي تجتازه العربة.
The research presents the design of a laboratory model to automate four traffic nodes using image processing - a proposal for a visual automated traffic system. By organizing the work of a traffic node, depending on the digital processing of the images of four cameras installed at the intersection.
Since Electroencephalogram (EEG) signals have very small magnitude, it's very hard
to capture these signals without having noise (produced by surrounding artifacts) affect the
real EEG signals, so it is necessary to use Filters to remove noise.
Th
is work proposes a design of an electronic circuit using a microcontroller, an
instrumentation amplifier and an operational amplifier able to capture EEG signals, convert
the captured signals from analog state to digital one and send the converted signal (digital
signal) to a group of three digital filters.
This paper gives a design of three digital elliptic filters ready to be used in real time
filtering of EEG signals (which preliminary represents the condition of the brain) making
the software part which complements the hardware part in the EEG signals capturing
system.
Finally we are going to show the way of using the designed electronic circuit with
the three designed digital filters, demonstrate and discuss the results of this work.
We have used Eagle 6.6 software to design and draw the circuit, CodeVision AVR
3.12 software to write the program downloaded on the microcontroller, Mathworks
MATLAB 2014a software to design the three digital filters and Mathworks MATLAB
2014a Simulink tool to make the appropriate experiments and get the results.
This research presents a mathematic module for stepper motor in Matlab program
through the equations that describe the motor transfer function. It illustrates the primary
characters of the open loop for the designed module, then it offers PID contr
oller design
for controlling the motor speed.
In addition, we can use the fuzzy logic and its applications in order to design a speed
fuzzy controller. Finally, we make a comparison between the fuzzy and PID controller in
control performance and response time.
The purpose of this article is to shed light on the mechanism
and the procedures of a neuro-fuzzy controller that classifies an
input face into any of the four facial expressions, which are
Happiness, Sadness, Anger and Fear. This program works
a
ccording to the facial characteristic points-FCP which is taken
from one side of the face, and depends, in contrast with some
traditional studies which rely on the whole face, on three
components: Eyebrows, Eyes and Mouth.
