Abstract: Battery storage system is emerging as an essential component of hybrid power system based on renewable energy resources such as solar and wind in order to make these sources dispatchable. Accurate modeling of battery storage system is ssential in order to ensure optimal planning of hybrid power systems incorporating battery storage. Majority of the system planning studies involving battery storage assume battery charging efficiency to be constant. However a strong correlation exists between battery charging efficiency and battery state of charge. In this work a Fuzzy logic based model has been presented for determining battery charging efficiency relative to a particular SOC. In order to demonstrate the efficacy of proposed approach, reliability evaluation studies are carried out for a hypothetical autonomous hybrid power system located in Jaisalmer, Rajasthan, India. The impact of considering battery charging efficiency as a function of state of charge is compared against the assumption of fixed battery charging efficiency for three different configurations comprising of wind-storage, solar-storage and wind-solar-storage.
Abstract: Project selection problems on management
information system (MIS) are often considered a multi-criteria
decision-making (MCDM) for a solving method. These problems
contain two aspects, such as interdependencies among criteria and
candidate projects and qualitative and quantitative factors of projects.
However, most existing methods reported in literature consider these
aspects separately even though these two aspects are simultaneously
incorporated. For this reason, we proposed a hybrid method using
analytic network process (ANP) and fuzzy logic in order to represent
both aspects. We then propose a goal programming model to conduct
an optimization for the project selection problems interpreted by a
hybrid concept. Finally, a numerical example is conducted as
verification purposes.
Abstract: The paper proposes a methodology to process the signals coming from the Transcranial Magnetic Stimulation (TMS) in order to identify the pathology and evaluate the therapy to treat the patients affected by demency diseases. In particular, a fuzzy model is developed to identify the demency of the patients affected by Subcortical Ischemic Vascular Dementia (SIVD) and to measure the effect of a repetitive TMS on their motor performances. A tool is also presented to support the mentioned analysis.
Abstract: Fuzzy logic can be used when knowledge is
incomplete or when ambiguity of data exists. The purpose of
this paper is to propose a proactive fuzzy set- based model for
reacting to the risk inherent in investment activities relative to
a complete view of portfolio management. Fuzzy rules are
given where, depending on the antecedents, the portfolio size
may be slightly or significantly decreased or increased. The
decision maker considers acceptable bounds on the proportion
of acceptable risk and return. The Fuzzy Controller model
allows learning to be achieved as 1) the firing strength of each
rule is measured, 2) fuzzy output allows rules to be updated,
and 3) new actions are recommended as the system continues
to loop. An extension is given to the fuzzy controller that
evaluates potential financial loss before adjusting the
portfolio. An application is presented that illustrates the
algorithm and extension developed in the paper.
Abstract: An active suspension system has been proposed to
improve the ride comfort. A quarter-car 2 degree-of-freedom (DOF)
system is designed and constructed on the basis of the concept of a
four-wheel independent suspension to simulate the actions of an
active vehicle suspension system. The purpose of a suspension
system is to support the vehicle body and increase ride comfort. The
aim of the work described in the paper was to illustrate the
application of fuzzy logic technique to the control of a continuously
damping automotive suspension system. The ride comfort is
improved by means of the reduction of the body acceleration caused
by the car body when road disturbances from smooth road and real
road roughness.
The paper describes also the model and controller used in the
study and discusses the vehicle response results obtained from a
range of road input simulations. In the conclusion, a comparison of
active suspension fuzzy control and Proportional Integration
derivative (PID) control is shown using MATLAB simulations.
Abstract: This paper presents anapproach of hybridizing two or more artificial intelligence (AI) techniques which arebeing used to
fuzzify the workstress level ranking and categorize the rating accordingly. The use of two or more techniques (hybrid approach)
has been considered in this case, as combining different techniques may lead to neutralizing each other-s weaknesses generating a
superior hybrid solution. Recent researches have shown that there is a
need for a more valid and reliable tools, for assessing work stress. Thus artificial intelligence techniques have been applied in this
instance to provide a solution to a psychological application. An overview about the novel and autonomous interactive model for analysing work-stress that has been developedusing multi-agent
systems is also presented in this paper. The establishment of the intelligent multi-agent decision analyser (IMADA) using hybridized technique of neural networks and fuzzy logic within the multi-agent based framework is also described.
Abstract: Fuzzy Load forecasting plays a paramount role in the operation and management of power systems. Accurate estimation of future power demands for various lead times facilitates the task of generating power reliably and economically. The forecasting of future loads for a relatively large lead time (months to few years) is studied here (long term load forecasting). Among the various techniques used in forecasting load, artificial intelligence techniques provide greater accuracy to the forecasts as compared to conventional techniques. Fuzzy Logic, a very robust artificial intelligent technique, is described in this paper to forecast load on long term basis. The paper gives a general algorithm to forecast long term load. The algorithm is an Extension of Short term load forecasting method to Long term load forecasting and concentrates not only on the forecast values of load but also on the errors incorporated into the forecast. Hence, by correcting the errors in the forecast, forecasts with very high accuracy have been achieved. The algorithm, in the paper, is demonstrated with the help of data collected for residential sector (LT2 (a) type load: Domestic consumers). Load, is determined for three consecutive years (from April-06 to March-09) in order to demonstrate the efficiency of the algorithm and to forecast for the next two years (from April-09 to March-11).
Abstract: Heating systems are a necessity for regions which
brace extreme cold weather throughout the year. To maintain a comfortable temperature inside a given place, heating systems
making use of- Hydronic boilers- are used. The principle of a single
pipe system serves as a base for their working. It is mandatory for these heating systems to control the room temperature, thus
maintaining a warm environment. In this paper, the concept of regulation of the room temperature over a wide range is established
by using an Adaptive Fuzzy Controller (AFC). This fuzzy controller automatically detects the changes in the outside temperatures and
correspondingly maintains the inside temperature to a palatial value. Two separate AFC's are put to use to carry out this function: one to
determine the quantity of heat needed to reach the prospective temperature required and to set the desired temperature; the other to control the position of the valve, which is directly proportional to the
error between the present room temperature and the user desired temperature. The fuzzy logic controls the position of the valve as per
the requirement of the heat. The amount by which the valve opens or closes is controlled by 5 knob positions, which vary from minimum to maximum, thereby regulating the amount of heat flowing through the valve. For the given test system data, different de-fuzzifier
methods have been implemented and the results are compared. In order to validate the effectiveness of the proposed approach, a fuzzy controller has been designed by obtaining a test data from a real time
system. The simulations are performed in MATLAB and are verified with standard system data. The proposed approach can be implemented for real time applications.
Abstract: Fuzzy controllers are potential candidates for the
control of nonlinear, time variant and also complicated systems. Anti
lock brake system (ABS) which is a nonlinear system, may not be
easily controlled by classical control methods. An intelligent Fuzzy
control method is very useful for this kind of nonlinear system. A
typical antilock brake system (ABS) by sensing the wheel lockup,
releases the brakes for a short period of time, and then reapplies again
the brakes when the wheel spins up. In this paper, an intelligent fuzzy
ABS controller is designed to adjust slipping performance for variety
of roads. There are tow major sections in the proposing control
system. First section consists of tow Fuzzy-Logic Controllers (FLC)
providing optimal brake torque for both front and rear wheels.
Second section which is also a FLC provides required amount of slip
and torque references properties for different kind of roads.
Simulation results of our proposed intelligent ABS for three different
kinds of road show more reliable and better performance in compare
with two other break systems.
Abstract: Recent developments in Soft computing techniques,
power electronic switches and low-cost computational hardware have
made it possible to design and implement sophisticated control
strategies for sensorless speed control of AC motor drives. Such an
attempt has been made in this work, for Sensorless Speed Control of
Induction Motor (IM) by means of Direct Torque Fuzzy Control
(DTFC), PI-type fuzzy speed regulator and MRAS speed estimator
strategy, which is absolutely nonlinear in its nature. Direct torque
control is known to produce quick and robust response in AC drive
system. However, during steady state, torque, flux and current ripple
occurs. So, the performance of conventional DTC with PI speed
regulator can be improved by implementing fuzzy logic techniques.
Certain important issues in design including the space vector
modulated (SVM) 3-Ф voltage source inverter, DTFC design,
generation of reference torque using PI-type fuzzy speed regulator
and sensor less speed estimator have been resolved. The proposed
scheme is validated through extensive numerical simulations on
MATLAB. The simulated results indicate the sensor less speed
control of IM with DTFC and PI-type fuzzy speed regulator provides
satisfactory high dynamic and static performance compare to
conventional DTC with PI speed regulator.
Abstract: One of the long standing challenging aspect in mobile robotics is the ability to navigate autonomously, avoiding modeled and unmodeled obstacles especially in crowded and unpredictably changing environment. A successful way of structuring the navigation task in order to deal with the problem is within behavior based navigation approaches. In this study, Issues of individual behavior design and action coordination of the behaviors will be addressed using fuzzy logic. A layered approach is employed in this work in which a supervision layer based on the context makes a decision as to which behavior(s) to process (activate) rather than processing all behavior(s) and then blending the appropriate ones, as a result time and computational resources are saved.
Abstract: This paper presents the idea of a rough controller with application to control the overhead traveling crane system. The structure of such a controller is based on a suggested concept of a fuzzy logic controller. A measure of fuzziness in rough sets is introduced. A comparison between fuzzy logic controller and rough controller has been demonstrated. The results of a simulation comparing the performance of both controllers are shown. From these results we infer that the performance of the proposed rough controller is satisfactory.
Abstract: A DC servomotor position control system using a Fuzzy Logic Sliding mode Model Following Control or FLSMFC approach is presented. The FLSMFC structure consists of an integrator and variable structure system. The integral control is introduced into it in order to eliminated steady state error due to step and ramp command inputs and improve control precision, while the fuzzy control would maintain the insensitivity to parameter variation and disturbances. The FLSMFC strategy is implemented and applied to a position control of a DC servomotor drives. Experimental results indicated that FLSMFC system performance with respect to the sensitivity to parameter variations is greatly reduced. Also, excellent control effects and avoids the chattering phenomenon.
Abstract: Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.
Abstract: The load flow study in a power system constitutes a study of paramount importance. The study reveals the electrical performance and power flows (real and reactive) for specified condition when the system is operating under steady state. This paper gives an overview of different techniques used for load flow study under different specified conditions.
Abstract: In this paper, Neuro-Fuzzy based Fuzzy Subtractive
Clustering Method (FSCM) and Self Tuning Fuzzy PD-like
Controller (STFPDC) were used to solve non-linearity and trajectory
problems of pitch AND yaw angles of Twin Rotor MIMO system
(TRMS). The control objective is to make the beams of TRMS reach
a desired position quickly and accurately. The proposed method
could achieve control objectives with simpler controller. To simplify
the complexity of STFPDC, ANFIS based FSCM was used to
simplify the controller and improve the response. The proposed
controllers could achieve satisfactory objectives under different input
signals. Simulation results under MATLAB/Simulink® proved the
improvement of response and superiority of simplified STFPDC on
Fuzzy Logic Controller (FLC).
Abstract: The approach proposed here is oriented in the direction of fuzzy system for the analysis and the synthesis of intelligent climate controllers, the simulation of the internal climate of the greenhouse is achieved by a linear model whose coefficients are obtained by identification. The use of fuzzy logic controllers for the regulation of climate variables represents a powerful way to minimize the energy cost. Strategies of reduction and optimization are adopted to facilitate the tuning and to reduce the complexity of the controller.
Abstract: Information Technology (IT) projects are always
accompanied by various risks and because of high rate of failure in
such projects, managing risks in order to neutralize or at least
decrease their effects on the success of the project is strongly
essential. In this paper, fuzzy analytical hierarchy process (FAHP) is
exploited as a means of risk evaluation methodology to prioritize and
organize risk factors faced in IT projects. A real case of IT projects, a
project of design and implementation of an integrated information
system in a vehicle producing company in Iran is studied. Related
risk factors are identified and then expert qualitative judgments about
these factors are acquired. Translating these judgments to fuzzy
numbers and using them as an input to FAHP, risk factors are then
ranked and prioritized by FAHP in order to make project managers
aware of more important risks and enable them to adopt suitable
measures to deal with these highly devastative risks.
Abstract: The steady-state operation of maintaining voltage
stability is done by switching various controllers scattered all over
the power network. When a contingency occurs, whether forced or
unforced, the dispatcher is to alleviate the problem in a minimum
time, cost, and effort. Persistent problem may lead to blackout. The
dispatcher is to have the appropriate switching of controllers in terms
of type, location, and size to remove the contingency and maintain
voltage stability. Wrong switching may worsen the problem and that
may lead to blackout. This work proposed and used a Fuzzy CMeans
Clustering (FCMC) to assist the dispatcher in the decision
making. The FCMC is used in the static voltage stability to map
instantaneously a contingency to a set of controllers where the types,
locations, and amount of switching are induced.
Abstract: This paper presents the design and implementation of
the WebGD, a CORBA-based document classification and retrieval
system on Internet. The WebGD makes use of such techniques as Web,
CORBA, Java, NLP, fuzzy technique, knowledge-based processing
and database technology. Unified classification and retrieval model,
classifying and retrieving with one reasoning engine and flexible
working mode configuration are some of its main features. The
architecture of WebGD, the unified classification and retrieval model,
the components of the WebGD server and the fuzzy inference engine
are discussed in this paper in detail.