Abstract: In this paper, a novel fuzzy approach is developed
while solving the Dynamic Routing and Wavelength Assignment
(DRWA) problem in optical networks with Wavelength Division
Multiplexing (WDM). In this work, the effect of nonlinear and linear
impairments such as Four Wave Mixing (FWM) and amplifier
spontaneous emission (ASE) noise are incorporated respectively. The
novel algorithm incorporates fuzzy logic controller (FLC) to reduce
the effect of FWM noise and ASE noise on a requested lightpath
referred in this work as FWM aware fuzzy dynamic routing and
wavelength assignment algorithm. The FWM crosstalk products and
the static FWM noise power per link are pre computed in order to
reduce the set up time of a requested lightpath, and stored in an
offline database. These are retrieved during the setting up of a
lightpath and evaluated online taking the dynamic parameters like
cost of the links into consideration.
Abstract: This paper presents the advantages of fuzzy control use in technological processes control. The paper presents a real application of the Linguistic Fuzzy-Logic Control, developed at the University of Ostrava for the control of physical models in the Intelligent Systems Laboratory. The paper presents an example of a sensitive non-linear model, such as a magnetic levitation model and obtained results which show how modern information technologies can help to solve actual technical problems. A special method based on the LFLC controller with partial components is presented in this paper followed by the method of automatic context change, which is very helpful to achieve more accurate control results. The main advantage of the used system is its robustness in changing conditions demonstrated by comparing with conventional PID controller. This technology and real models are also used as a background for problem-oriented teaching, realized at the department for master students and their collaborative as well as individual final projects.
Abstract: Land reallocation is one of the most important steps in
land consolidation projects. Many different models were proposed for
land reallocation in the literature such as Fuzzy Logic, block priority
based land reallocation and Spatial Decision Support Systems. A
model including four parts is considered for automatic block
reallocation with genetic algorithm method in land consolidation
projects. These stages are preparing data tables for a project land,
determining conditions and constraints of land reallocation, designing
command steps and logical flow chart of reallocation algorithm and
finally writing program codes of Genetic Algorithm respectively. In
this study, we designed the first three steps of the considered model
comprising four steps.
Abstract: Hybrid electric vehicles can reduce pollution and
improve fuel economy. Power-split hybrid electric vehicles (HEVs)
provide two power paths between the internal combustion engine
(ICE) and energy storage system (ESS) through the gears of an
electrically variable transmission (EVT). EVT allows ICE to operate
independently from vehicle speed all the time. Therefore, the ICE can
operate in the efficient region of its characteristic brake specific fuel
consumption (BSFC) map. The two-mode powertrain can operate in
input-split or compound-split EVT modes and in four different fixed
gear configurations. Power-split architecture is advantageous because
it combines conventional series and parallel power paths. This
research focuses on input-split and compound-split modes in the
two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an
internal combustion engine (ICE) and PI control for electric machines
(EMs) are derived for the urban driving cycle simulation. These
control algorithms reduce vehicle fuel consumption and improve ICE
efficiency while maintaining the state of charge (SOC) of the energy
storage system in an efficient range.
Abstract: This article presents two methods for the
compensation of harmonics generated by a nonlinear load. The first is
the classic method P-Q. The second is the controller by modern
method of artificial intelligence specifically fuzzy logic. Both
methods are applied to a shunt Active Power Filter (sAPF) based on a
three-phase voltage converter at five levels NPC topology. In
calculating the harmonic currents of reference, we use the algorithm
P-Q and pulse generation, we use the intersective PWM. For
flexibility and dynamics, we use fuzzy logic. The results give us clear
that the rate of Harmonic Distortion issued by fuzzy logic is better
than P-Q.
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: 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 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: Ti6Al4V alloy is highly used in the automotive and
aerospace industry due to its good machining characteristics. Micro
EDM drilling is commonly used to drill micro hole on extremely hard
material with very high depth to diameter ratio. In this study, the
parameters of micro-electrical discharge machining (EDM) in drilling
of Ti6Al4V alloy is optimized for higher machining accuracy with
less hole-dilation and hole taper ratio. The micro-EDM machining
parameters includes, peak current and pulse on time. Fuzzy analysis
was developed to evaluate the machining accuracy. The analysis
shows that hole-dilation and hole-taper ratio are increased with the
increasing of peak current and pulse on time. However, the surface
quality deteriorates as the peak current and pulse on time increase.
The combination that gives the optimum result for hole dilation is
medium peak current and short pulse on time. Meanwhile, the
optimum result for hole taper ratio is low peak current and short pulse
on time.
Abstract: Self-compacting concrete (SCC) developed in Japan
in the late 80s has enabled the construction industry to reduce
demand on the resources, improve the work condition and also
reduce the impact of environment by elimination of the need for
compaction. Fuzzy logic (FL) approaches has recently been used to
model some of the human activities in many areas of civil
engineering applications. Especially from these systems in the model
experimental studies, very good results have been obtained. In the
present study, a model for predicting compressive strength of SCC
containing various proportions of fly ash, as partial replacement of
cement has been developed by using Fuzzy Inference System (FIS).
For the purpose of building this model, a database of experimental
data were gathered from the literature and used for training and
testing the model. The used data as the inputs of fuzzy logic models
are arranged in a format of five parameters that cover the total binder
content, fly ash replacement percentage, water content,
superplasticizer and age of specimens. The training and testing results
in the fuzzy logic model have shown a strong potential for predicting
the compressive strength of SCC containing fly ash in the considered
range.
Abstract: The inspection of underneath vehicle system has been
given significant attention by governments after the threat of
terrorism become more prevalent. New technologies such as mobile
robots and computer vision are led to have more secure environment.
This paper proposed that a mobile robot like Aria robot can be used
to search and inspect the bombs under parking a lot vehicle. This
robot is using fuzzy logic and subsumption algorithms to control the
robot that movies underneath the vehicle. An OpenCV library and
laser Hokuyo are added to Aria robot to complete the experiment for
under vehicle inspection. This experiment was conducted at the
indoor environment to demonstrate the efficiency of our methods to
search objects and control the robot movements under vehicle. We
got excellent results not only by controlling the robot movement but
also inspecting object by the robot camera at same time. This success
allowed us to know the requirement to construct a new cost effective
robot with more functionality.
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: This paper presents a hybrid fuzzy logic control
strategy for a unicycle trajectory following robot on irregular terrains.
In literature, researchers have presented the design of path tracking
controllers of mobile robots on non-frictional surface. In this work,
the robot is simulated to drive on irregular terrains with contrasting
frictional profiles of peat and rough gravel. A hybrid fuzzy logic
controller is utilised to stabilise and drive the robot precisely with the
predefined trajectory and overcome the frictional impact. The
controller gains and scaling factors were optimised using spiral
dynamics optimisation algorithm to minimise the mean square error
of the linear and angular velocities of the unicycle robot. The robot
was simulated on various frictional surfaces and terrains and the
controller was able to stabilise the robot with a superior performance
that is shown via simulation results.
Abstract: This paper explains about the voltage output for DC to
DC boost converter between open loop, PID controller and fuzzy
logic controller through Matlab Simulink. Simulink input voltage was
set at 12V and the voltage reference was set at 24V. The analysis on
the deviation of voltage resulted that the difference between reference
voltage setting and the output voltage is always lower. Comparison
between open loop, PID and FLC shows that, the open loop circuit
having a bit higher on the deviation of voltage. The PID circuit
boosts for FLC has a lesser deviation of voltage and proved that it is
such a better performance on control the deviation of voltage during
the boost mode.
Abstract: The assessment of the risk posed by a borrower to a
lender is one of the common problems that financial institutions have
to deal with. Consumers vying for a mortgage are generally
compared to each other by the use of a number called the Credit
Score, which is generated by applying a mathematical algorithm to
information in the applicant’s credit report. The higher the credit
score, the lower the risk posed by the candidate, and the better he is
to be taken on by the lender. The objective of the present work is to
use fuzzy logic and linguistic rules to create a model that generates
Credit Scores.
Abstract: In this paper, we propose a multi-agent intelligent
system that is used for monitoring the health conditions of elderly
people. Monitoring the health condition of elderly people is a
complex problem that involves different medical units and requires
continuous monitoring. Such expert system is highly needed in rural
areas because of inadequate number of available specialized
physicians or nurses. Such monitoring must have autonomous
interactions between these medical units in order to be effective. A
multi-agent system is formed by a community of agents that
exchange information and proactively help one another to achieve the
goal of elderly monitoring. The agents in the developed system are
equipped with intelligent decision maker that arms them with the
rule-based reasoning capability that can assist the physicians in
making decisions regarding the medical condition of elderly people.
Abstract: The construction of a new airport or the extension of
an existing one requires massive investments and many times public
private partnerships were considered in order to make feasible such
projects. One characteristic of these projects is uncertainty with
respect to financial and environmental impacts on the medium to long
term. Another one is the multistage nature of these types of projects.
While many airport development projects have been a success, some
others have turned into a nightmare for their promoters.
This communication puts forward a new approach for airport
investment risk assessment. The approach takes explicitly into
account the degree of uncertainty in activity levels prediction and
proposes milestones for the different stages of the project for
minimizing risk. Uncertainty is represented through fuzzy dual theory
and risk management is performed using dynamic programming. An
illustration of the proposed approach is provided.
Abstract: Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.
Abstract: In terms of ecology forecast effects of desertification, the purpose of this study is to develop a predictive model of growth and adaptation of species in arid environment and bioclimatic conditions. The impact of climate change and the desertification phenomena is the result of combined effects in magnitude and frequency of these phenomena. Like the data involved in the phytopathogenic process and bacteria growth in arid soil occur in an uncertain environment because of their complexity, it becomes necessary to have a suitable methodology for the analysis of these variables. The basic principles of fuzzy logic those are perfectly suited to this process. As input variables, we consider the physical parameters, soil type, bacteria nature, and plant species concerned. The result output variable is the adaptability of the species expressed by the growth rate or extinction. As a conclusion, we prevent the possible strategies for adaptation, with or without shifting areas of plantation and nature adequate vegetation.
Abstract: It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.