Abstract: In this study, we proposed two techniques to track the
maximum power point (MPPT) of a photovoltaic system. The first is
an intelligent control technique, and the second is robust used for
variable structure system. In fact the characteristics I-V and P–V of
the photovoltaic generator depends on the solar irradiance and
temperature. These climate changes cause the fluctuation of
maximum power point; a maximum power point tracking technique
(MPPT) is required to maximize the output power. For this we have
adopted a control by fuzzy logic (FLC) famous for its stability and
robustness. And a Siding Mode Control (SMC) widely used for
variable structure system. The system comprises a photovoltaic panel
(PV), a DC-DC converter, which is considered as an adaptation stage
between the PV and the load. The modelling and simulation of the
system is developed using MATLAB/Simulink. SMC technique
provides a good tracking speed in fast changing irradiation and when
the irradiation changes slowly or it is constant the panel power of
FLC technique presents a much smoother signal with less
fluctuations.
Abstract: This paper presents the development of a robot car
that can track the motion of an object by detecting its color through
an Android device. The employed computer vision algorithm uses the
OpenCV library, which is embedded into an Android application of a
smartphone, for manipulating the captured image of the object. The
captured image of the object is subjected to color conversion and is
transformed to a binary image for further processing after color
filtering. The desired object is clearly determined after removing
pixel noise by applying image morphology operations and contour
definition. Finally, the area and the center of the object are
determined so that object’s motion to be tracked. The smartphone
application has been placed on a robot car and transmits by Bluetooth
to an Arduino assembly the motion directives so that to follow
objects of a specified color. The experimental evaluation of the
proposed algorithm shows reliable color detection and smooth
tracking characteristics.
Abstract: The paper presents a method for a simple and
immediate motion planning of a SCARA robot, whose end-effector
has to move along a given trajectory; the calculation procedure
requires the user to define in analytical form or by points the
trajectory to be followed and to assign the curvilinear abscissa as
function of the time. On the basis of the geometrical characteristics
of the robot, a specifically developed program determines the motion
laws of the actuators that enable the robot to generate the required
movement; this software can be used in all industrial applications for
which a SCARA robot has to be frequently reprogrammed, in order
to generate various types of trajectories with different motion times.
Abstract: In this contribution a structure for high level lateral vehicle tracking control based on the disturbance observer is presented. The structure is characterized by stationary compensating side forces disturbances and guaranteeing a cooperative behavior at the same time. Driver inputs are not compensated by the disturbance observer. Moreover the structure is especially useful as it robustly stabilizes the vehicle. Therefore the parameters are selected using the Parameter Space Approach. The implemented algorithms are tested in real world scenarios.
Abstract: In this paper we propose a discrete tracking control of
nonholonomic mobile robots with two degrees of freedom. The
electromechanical model of a mobile robot moving on a horizontal
surface without slipping, with two rear wheels controlled by two
independent DC electric, and one front roal wheel is considered. We
present backstepping design based on the Euler approximate discretetime
model of a continuous-time plant. Theoretical considerations are
verified by numerical simulation.
Abstract: In this paper, we discuss the performance of applying
hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation
algorithm on an intelligent controller for a differential drive robot. A
unicycle class of differential drive robot is utilised to serve as a basis
application to evaluate the performance of the HSDBC algorithm. A
hybrid fuzzy logic controller is developed and implemented for the
unicycle robot to follow a predefined trajectory. Trajectories of
various frictional profiles and levels were simulated to evaluate the
performance of the robot at different operating conditions. Controller
gains and scaling factors were optimised using HSDBC and the
performance is evaluated in comparison to previously adopted
optimisation algorithms. The HSDBC has proven its feasibility in
achieving a faster convergence toward the optimal gains and resulted
in a superior performance.
Abstract: The detection of moving objects from a video image
sequences is very important for object tracking, activity recognition,
and behavior understanding in video surveillance.
The most used approach for moving objects detection / tracking is
background subtraction algorithms. Many approaches have been
suggested for background subtraction. But, these are illumination
change sensitive and the solutions proposed to bypass this problem
are time consuming.
In this paper, we propose a robust yet computationally efficient
background subtraction approach and, mainly, focus on the ability to
detect moving objects on dynamic scenes, for possible applications in
complex and restricted access areas monitoring, where moving and
motionless persons must be reliably detected. It consists of three
main phases, establishing illumination changes invariance,
background/foreground modeling and morphological analysis for
noise removing.
We handle illumination changes using Contrast Limited Histogram
Equalization (CLAHE), which limits the intensity of each pixel to
user determined maximum. Thus, it mitigates the degradation due to
scene illumination changes and improves the visibility of the video
signal. Initially, the background and foreground images are extracted
from the video sequence. Then, the background and foreground
images are separately enhanced by applying CLAHE.
In order to form multi-modal backgrounds we model each channel
of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture
Model (GMM). Finally, we post process the resulting binary
foreground mask using morphological erosion and dilation
transformations to remove possible noise.
For experimental test, we used a standard dataset to challenge the
efficiency and accuracy of the proposed method on a diverse set of
dynamic scenes.
Abstract: The pursuit of the MPPT has led to the development of many kinds of controllers, one of which is the Fuzzy Logic controller, which has proven its worth. To further tune this controller this paper will discuss and analyze the use of Genetic Algorithms to tune the Fuzzy Logic Controller. It will provide an introduction to both systems, and test their compatibility and performance.
Abstract: This paper describes the tradeoffs and the design from
scratch of a self-contained, easy-to-use health dashboard software
system that provides customizable data tracking for patients in smart
homes. The system is made up of different software modules and
comprises a front-end and a back-end component. Built with HTML,
CSS, and JavaScript, the front-end allows adding users, logging into
the system, selecting metrics, and specifying health goals. The backend
consists of a NoSQL Mongo database, a Python script, and a
SimpleHTTPServer written in Python. The database stores user
profiles and health data in JSON format. The Python script makes use
of the PyMongo driver library to query the database and displays
formatted data as a daily snapshot of user health metrics against
target goals. Any number of standard and custom metrics can be
added to the system, and corresponding health data can be fed
automatically, via sensor APIs or manually, as text or picture data
files. A real-time METAR request API permits correlating weather
data with patient health, and an advanced query system is
implemented to allow trend analysis of selected health metrics over
custom time intervals. Available on the GitHub repository system,
the project is free to use for academic purposes of learning and
experimenting, or practical purposes by building on it.
Abstract: Human motion capture has become one of the major
area of interest in the field of computer vision. Some of the major
application areas that have been rapidly evolving include the
advanced human interfaces, virtual reality and security/surveillance
systems. This study provides a brief overview of the techniques and
applications used for the markerless human motion capture, which
deals with analyzing the human motion in the form of mathematical
formulations. The major contribution of this research is that it
classifies the computer vision based techniques of human motion
capture based on the taxonomy, and then breaks its down into four
systematically different categories of tracking, initialization, pose
estimation and recognition. The detailed descriptions and the
relationships descriptions are given for the techniques of tracking and
pose estimation. The subcategories of each process are further
described. Various hypotheses have been used by the researchers in
this domain are surveyed and the evolution of these techniques have
been explained. It has been concluded in the survey that most
researchers have focused on using the mathematical body models for
the markerless motion capture.
Abstract: A model reference adaptive control and a fixed gain
LQR control were implemented in the height controller of a quadrotor
that has parametric uncertainties due to the act of picking up an
object of unknown dimension and mass. It is shown that an adaptive
controller, unlike the fixed gain controller, is capable of ensuring a
stable tracking performance under such condition, although adaptive
control suffers from several limitations. The combination of both
adaptive and fixed gain control in the controller architecture can
result in an enhanced tracking performance in the presence parametric
uncertainties.
Abstract: Performance of different filtering approaches depends
on modeling of dynamical system and algorithm structure. For
modeling and smoothing the data the evaluation of posterior
distribution in different filtering approach should be chosen carefully.
In this paper different filtering approaches like filter KALMAN,
EKF, UKF, EKS and smoother RTS is simulated in some trajectory
tracking of path and accuracy and limitation of these approaches are
explained. Then probability of model with different filters is
compered and finally the effect of the noise variance to estimation is
described with simulations results.
Abstract: Motion Tracking and Stereo Vision are complicated,
albeit well-understood problems in computer vision. Existing
softwares that combine the two approaches to perform stereo motion
tracking typically employ complicated and computationally expensive
procedures. The purpose of this study is to create a simple and
effective solution capable of combining the two approaches. The
study aims to explore a strategy to combine the two techniques
of two-dimensional motion tracking using Kalman Filter; and depth
detection of object using Stereo Vision. In conventional approaches
objects in the scene of interest are observed using a single camera.
However for Stereo Motion Tracking; the scene of interest is
observed using video feeds from two calibrated cameras. Using two
simultaneous measurements from the two cameras a calculation for
the depth of the object from the plane containing the cameras is made.
The approach attempts to capture the entire three-dimensional spatial
information of each object at the scene and represent it through a
software estimator object. In discrete intervals, the estimator tracks
object motion in the plane parallel to plane containing cameras and
updates the perpendicular distance value of the object from the plane
containing the cameras as depth. The ability to efficiently track
the motion of objects in three-dimensional space using a simplified
approach could prove to be an indispensable tool in a variety of
surveillance scenarios. The approach may find application from high
security surveillance scenes such as premises of bank vaults, prisons
or other detention facilities; to low cost applications in supermarkets
and car parking lots.
Abstract: Testing the first year students of Informatics at the
University of Debrecen revealed that students start their tertiary
studies in programming with a low level of programming knowledge
and algorithmic skills. The possible reasons which lead the students
to this very unfortunate result were examined. The results of the test
were compared to the students’ results in the school leaving exams
and to their self-assessment values. It was found that there is only a
slight connection between the students’ results in the test and in the
school leaving exams, especially at intermediate level. Beyond this,
the school leaving exams do not seem to enable students to evaluate
their own abilities.
Abstract: The most important component affecting the
efficiency of photovoltaic power systems are solar panels. In other
words, efficiency of these systems are significantly affected due to
the being low efficiency of solar panel. Thus, solar panels should be
operated under maximum power point conditions through a power
converter. In this study, design of boost converter has been carried
out with maximum power point tracking (MPPT) algorithm which is
incremental conductance (Inc-Cond). By using this algorithm,
importance of power converter in MPPT hardware design, impacts of
MPPT operation have been shown. It is worth noting that initial
operation point is the main criteria for determining the MPPT
performance. In addition, it is shown that if value of load resistance is
lower than critical value, failure operation is realized. For these
analyzes, direct duty control is used for simplifying the control.
Abstract: Nowadays, Photovoltaic-PV Farms/ Parks and large
PV-Smart Grid Interface Schemes are emerging and commonly
utilized in Renewable Energy distributed generation. However, PVhybrid-
Dc-Ac Schemes using interface power electronic converters
usually has negative impact on power quality and stabilization of
modern electrical network under load excursions and network fault
conditions in smart grid. Consequently, robust FACTS based
interface schemes are required to ensure efficient energy utilization
and stabilization of bus voltages as well as limiting switching/fault
onrush current condition. FACTS devices are also used in smart grid-
Battery Interface and Storage Schemes with PV-Battery Storage
hybrid systems as an elegant alternative to renewable energy
utilization with backup battery storage for electric utility energy and
demand side management to provide needed energy and power
capacity under heavy load conditions. The paper presents a robust
interface PV-Li-Ion Battery Storage Interface Scheme for
Distribution/Utilization Low Voltage Interface using FACTS
stabilization enhancement and dynamic maximum PV power tracking
controllers.
Digital simulation and validation of the proposed scheme is done
using MATLAB/Simulink software environment for Low Voltage-
Distribution/Utilization system feeding a hybrid Linear-Motorized
inrush and nonlinear type loads from a DC-AC Interface VSC-6-
pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion
Storage Battery.
Abstract: Among modern airflow measurement methods,
Particle Image Velocimetry (PIV) and Particle Tracking Velocimetry
(PTV), as visualized and non-instructive measurement techniques, are
playing more important role. This paper conducts a comparative
experimental study for airflow measurement employing both
techniques with the same condition. Velocity vector fields, velocity
contour fields, voticity profiles and turbulence profiles are selected as
the comparison indexes. The results show that the performance of both
PIV and PTV techniques for airflow measurement is satisfied, but
some differences between the both techniques are existed, it suggests
that selecting the measurement technique should be based on a
comprehensive consideration.
Abstract: This paper proposes a new technique to design a
fixed-structure robust loop shaping controller for the pneumatic
servosystem. In this paper, a new method based on a particle swarm
optimization (PSO) algorithm for tuning the weighting function
parameters to design an H∞ controller is presented. The PSO
algorithm is used to minimize the infinity norm of the transfer
function of the nominal closed loop system to obtain the optimal
parameters of the weighting functions. The optimal stability margin is
used as an objective in PSO for selecting the optimal weighting
parameters; it is shown that the proposed method can simplify the
design procedure of H∞ control to obtain optimal robust controller for
pneumatic servosystem. In addition, the order of the proposed
controller is much lower than that of the conventional robust loop
shaping controller, making it easy to implement in practical works.
Also two-degree-of-freedom (2DOF) control design procedure is
proposed to improve tracking performance in the face of noise and
disturbance. Result of simulations demonstrates the advantages of the
proposed controller in terms of simple structure and robustness
against plant perturbations and disturbances.
Abstract: The electric power supplied by a photovoltaic power
generation systems depends on the solar irradiation and temperature.
The PV system can supply the maximum power to the load at a
particular operating point which is generally called as maximum
power point (MPP), at which the entire PV system operates with
maximum efficiency and produces its maximum power. Hence, a
Maximum power point tracking (MPPT) methods are used to
maximize the PV array output power by tracking continuously the
maximum power point. The proposed MPPT controller is designed
for 10kW solar PV system installed at Cape Institute of Technology.
This paper presents the fuzzy logic based MPPT algorithm. However,
instead of one type of membership function, different structures of
fuzzy membership functions are used in the FLC design. The
proposed controller is combined with the system and the results are
obtained for each membership functions in Matlab/Simulink
environment. Simulation results are decided that which membership
function is more suitable for this system.
Abstract: Aim of this work was to study the genetic basis for oil
accumulation in olive fruit via tracking DGAT2 (Diacylglycerol
acyltransferase type-2) gene in three Egyptian Origen Olive cultivars
namely Toffahi, Hamed and Maraki using molecular marker
techniques and bioinformatics tools. Results illustrate that, firstly:
specific genomic band of Maraki cultivars was identified as DGAT2
(Diacylglycerol acyltransferase type-2) and identical for this gene in
Olea europaea with 100% of similarity. Secondly, differential
genomic band of Maraki cultivars which produced from RAPD
fingerprinting technique reflected predicted distinguished sequence
which identified as DGAT2 (Diacylglycerol acyltransferase type-2)
in Fragaria vesca subsp. Vesca with 76% of sequential similarity.
Third and finally, specific genomic specific band of Hamed cultivars
was identified as two fragments, 1- Olea europaea cultivar Koroneiki
diacylglycerol acyltransferase type 2 mRNA, complete cds with two
matches regions with 99% or 2- Predicted: Fragaria vesca subsp.
vesca diacylglycerol O-acyltransferase 2-like (LOC101313050),
mRNA with 86 % of similarity.