Abstract: Bidirectional energy transfer capability with high efficiency and reduced cost is fast gaining prominence in the central part of a lot of power conversion systems in Direct Current (DC) microgrid. Preferably, under the economics constraints, these systems utilise a single high efficiency power electronics conversion system and a dual active bridge converter. In this paper, modeling and performance of Dual Active Bridge (DAB) converter with Extended Phase Shift (EPS) is evaluated with two batteries on both sides of DC bus and bidirectional energy transfer is facilitated and this is further compared with the Single Phase Shift (SPS) mode of operation. Optimum operating zone is identified through exhaustive simulations using MATLAB/Simulink and SimPowerSystem software. Reduced rules based fuzzy logic controller is implemented for closed loop control of DAB converter. The control logic enables the bidirectional energy transfer within the batteries even at lower duty ratios. Charging and discharging of batteries is supervised by the fuzzy logic controller. State of charge, current and voltage for both the batteries are plotted in the battery characteristics. Power characteristics of batteries are also obtained using MATLAB simulations.
Abstract: Fully autonomous small Unmanned Aerial Vehicles
(UAVs) are increasingly being used in many commercial applications.
Although a lot of research has been done to develop safe, reliable
and durable UAVs, accidents due to electronic and structural failures
are not uncommon and pose a huge safety risk to the UAV operators
and the public. Hence there is a strong need for an automated health
monitoring system for UAVs with a view to minimizing mission
failures thereby increasing safety. This paper describes our approach
to monitoring the electronic and structural components in a small
UAV without the need for additional sensors to do the monitoring.
Our system monitors data from four sources; sensors, navigation
algorithms, control inputs from the operator and flight controller
outputs. It then does statistical analysis on the data and applies
a rule based engine to detect failures. This information can then
be fed back into the UAV and a decision to continue or abort the
mission can be taken automatically by the UAV and independent of
the operator. Our system has been verified using data obtained from
real flights over the past year from UAVs of various sizes that have
been designed and deployed by us for various applications.
Abstract: In aircraft design, the jump from the conceptual to
preliminary design stage introduces a level of complexity which
cannot be realistically handled by a single optimiser, be that a
human (chief engineer) or an algorithm. The design process is often
partitioned along disciplinary lines, with each discipline given a level
of autonomy. This introduces a number of challenges including, but
not limited to: coupling of design variables; coordinating disciplinary
teams; handling of large amounts of analysis data; reaching an
acceptable design within time constraints. A number of classical
Multidisciplinary Design Optimisation (MDO) architectures exist in
academia specifically designed to address these challenges. Their
limited use in the industrial aircraft design process has inspired
the authors of this paper to develop an alternative strategy based
on well established ideas from Decision Support Systems. The
proposed rule based architecture sacrifices possibly elusive guarantees
of convergence for an attractive return in simplicity. The method
is demonstrated on analytical and aircraft design test cases and its
performance is compared to a number of classical distributed MDO
architectures.
Abstract: Learning outcomes of a course (CLOs) and the abilities at the time of graduation referred to as Student Outcomes (SOs) are required to be assessed for ABET accreditation. A question in an assessment must target a CLO as well as an SO and must represent a required level of competence. This paper presents the idea of an Expert System (ES) to select a proper question to satisfy ABET accreditation requirements. For ES implementation, seven attributes of a question are considered including the learning outcomes and Bloom’s Taxonomy level. A database contains all the data about a course including course content topics, course learning outcomes and the CLO-SO relationship matrix. The knowledge base of the presented ES contains a pool of questions each with tags of the specified attributes. Questions and the attributes represent expert opinions. With implicit rule base the inference engine finds the best possible question satisfying the required attributes. It is shown that the novel idea of such an ES can be implemented and applied to a course with success. An application example is presented to demonstrate the working of the proposed ES.
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: The use of anatomical landmarks as a basis for image to patient registration is appealing because the registration may be performed retrospectively. We have previously proposed the use of two anatomical soft tissue landmarks of the head, the canthus (corner of the eye) and the tragus (a small, pointed, cartilaginous flap of the ear), as a registration basis for an automated CT image to patient registration system, and described their localization in patient space using close range photogrammetry. In this paper, the automatic localization of these landmarks in CT images, based on their curvature saliency and using a rule based system that incorporates prior knowledge of their characteristics, is described. Existing approaches to landmark localization in CT images are predominantly semi-automatic and primarily for localizing internal landmarks. To validate our approach, the positions of the landmarks localized automatically and manually in near isotropic CT images of 102 patients were compared. The average difference was 1.2mm (std = 0.9mm, max = 4.5mm) for the medial canthus and 0.8mm (std = 0.6mm, max = 2.6mm) for the tragus. The medial canthus and tragus can be automatically localized in CT images, with performance comparable to manual localization, based on the approach presented.
Abstract: This paper is based on the performance of the Switched Reluctance Motor (SRM) drives using Z-Source Inverter with the simplified rule base of Fuzzy Logic Controller (FLC) with the output scaling factor (SF) self-tuning mechanism are proposed. The aim of this paper is to simplify the program complexity of the controller by reducing the number of fuzzy sets of the membership functions (MFs) without losing the system performance and stability via the adjustable controller gain. ZSI exhibits both voltage-buck and voltage-boost capability. It reduces line harmonics, improves reliability, and extends output voltage range. The output SF of the controller can be tuned continuously by a gain updating factor, whose value is derived from fuzzy logic, with the plant error and error change ratio as input variables. Then the results, carried out on a four-phase 6/8 pole SRM based on the dSPACEDS1104 platform, to show the feasibility and effectiveness of the devised methods and also performance of the proposed controllers will be compared with conventional counterpart.
Abstract: A reconfigurable manufacturing system (RMS) is an
advanced system designed at the outset for rapid changes in its hardware
and software components in order to quickly adjust its production
capacity and functionally. Among various operational decisions, this
study considers the scheduling problem that determines the input
sequence and schedule at the same time for a given set of parts. In
particular, we consider the practical constraints that the numbers of
pallets/fixtures are limited and hence a part can be released into the
system only when the fixture required for the part is available. To
solve the integrated input sequencing and scheduling problems, we
suggest a priority rule based approach in which the two sub-problems
are solved using a combination of priority rules. To show the effectiveness
of various rule combinations, a simulation experiment was
done on the data for a real RMS, and the test results are reported.
Abstract: Internet is one of the major sources of information for
the person belonging to almost all the fields of life. Major language
that is used to publish information on internet is language. This thing
becomes a problem in a country like Pakistan, where Urdu is the
national language. Only 10% of Pakistan mass can understand
English. The reason is millions of people are deprived of precious
information available on internet. This paper presents a system for
translation from English to Urdu. A module LESSA is used that uses
a rule based algorithm to read the input text in English language,
understand it and translate it into Urdu language. The designed
approach was further incorporated to translate the complete website
from English language o Urdu language. An option appears in the
browser to translate the webpage in a new window. The designed
system will help the millions of users of internet to get benefit of the
internet and approach the latest information and knowledge posted
daily on internet.
Abstract: Economic models are complex dynamic systems with a lot of uncertainties and fuzzy data. Conventional modeling approaches using well known methods and techniques cannot provide realistic and satisfactory answers to today-s challenging economic problems. Qualitative modeling using fuzzy logic and intelligent system theories can be used to model macroeconomic models. Fuzzy Cognitive maps (FCM) is a new method been used to model the dynamic behavior of complex systems. For the first time FCMs and the Mamdani Model of Intelligent control is used to model macroeconomic models. This new model is referred as the Mamdani Rule-Based Fuzzy Cognitive Map (MBFCM) and provides the academic and research community with a new promising integrated advanced computational model. A new economic model is developed for a qualitative approach to Macroeconomic modeling. Fuzzy Controllers for such models are designed. Simulation results for an economic scenario are provided and extensively discussed
Abstract: This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.
Abstract: In practice, we often come across situations where it is
necessary to make decisions based on incomplete or uncertain data.
In control systems it may be due to the unknown exact mathematical
model, or its excessive complexity (e.g. nonlinearity) when it is
necessary to simplify it, respectively, to solve it using a rule base. In
the case of databases, searching data we compare a similarity
measure with of the requirements of the selection with stored data,
where both the select query and the data itself may contain vague
terms, for example in the form of linguistic qualifiers. In this paper,
we focus on the processing of uncertain data in databases and
demonstrate it on the example multi-criteria decision making in the
selection of variants, specified by higher number of technical
parameters.
Abstract: In this paper the application of rule mining in order to
review the effective factors on supplier selection is reviewed in the
following three sections 1) criteria selecting and information
gathering 2) performing association rule mining 3) validation and
constituting rule base. Afterwards a few of applications of rule base
is explained. Then, a numerical example is presented and analyzed
by Clementine software. Some of extracted rules as well as the
results are presented at the end.
Abstract: This paper proposes a Fuzzy Expert System design to
determine the wearing properties of nitrided and non nitrided steel.
The proposed Fuzzy Expert System approach helps the user and the
manufacturer to forecast the wearing properties of nitrided and non
nitrided steel under specified laboratory conditions. Surfaces of the
engineering components are often nitrided for improving wear,
corosion, fatigue specifications. A major property of nitriding
process is reducing distortion and wearing of the metalic alloys. A
Fuzzy Expert System was developed for determining the wearing and
durability properties of nitrided and non nitrided steels that were
tested under different loads and different sliding speeds in the
laboratory conditions.
Abstract: This paper focuses on the data-driven generation
of fuzzy IF...THEN rules. The resulted fuzzy rule base can be
applied to build a classifier, a model used for prediction, or
it can be applied to form a decision support system. Among
the wide range of possible approaches, the decision tree and
the association rule based algorithms are overviewed, and two
new approaches are presented based on the a priori fuzzy
clustering based partitioning of the continuous input variables.
An application study is also presented, where the developed
methods are tested on the well known Wisconsin Breast Cancer
classification problem.
Abstract: The genetic algorithm (GA) based solution techniques
are found suitable for optimization because of their ability of
simultaneous multidimensional search. Many GA-variants have been
tried in the past to solve optimal power flow (OPF), one of the
nonlinear problems of electric power system. The issues like
convergence speed and accuracy of the optimal solution obtained
after number of generations using GA techniques and handling
system constraints in OPF are subjects of discussion. The results
obtained for GA-Fuzzy OPF on various power systems have shown
faster convergence and lesser generation costs as compared to other
approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF)
using penalty factors to handle line flow constraints and load
bus voltage limits for both normal network and contingency case
with congestion. In addition to crossover and mutation rate
adaptation scheme that adapts crossover and mutation probabilities
for each generation based on fitness values of previous generations, a
block swap operator is also incorporated in proposed EGA-OPF. The
line flow limits and load bus voltage magnitude limits are handled by
incorporating line overflow and load voltage penalty factors
respectively in each chromosome fitness function. The effects of
different penalty factors settings are also analyzed under contingent
state.
Abstract: In this paper performance of Puma 560
manipulator is being compared for hybrid gradient descent
and least square method learning based ANFIS controller with
hybrid Genetic Algorithm and Generalized Pattern Search
tuned radial basis function based Neuro-Fuzzy controller.
ANFIS which is based on Takagi Sugeno type Fuzzy
controller needs prior knowledge of rule base while in radial
basis function based Neuro-Fuzzy rule base knowledge is not
required. Hybrid Genetic Algorithm with generalized Pattern
Search is used for tuning weights of radial basis function
based Neuro- fuzzy controller. All the controllers are checked
for butterfly trajectory tracking and results in the form of
Cartesian and joint space errors are being compared. ANFIS
based controller is showing better performance compared to
Radial Basis Function based Neuro-Fuzzy Controller but rule
base independency of RBF based Neuro-Fuzzy gives it an
edge over ANFIS
Abstract: This paper shows possibility of extraction Social,
Group and Individual Mind from Multiple Agents Rule Bases. Types
those Rule bases are selected as two fuzzy systems, namely
Mambdani and Takagi-Sugeno fuzzy system. Their rule bases are
describing (modeling) agent behavior. Modifying of agent behavior
in the time varying environment will be provided by learning fuzzyneural
networks and optimization of their parameters with using
genetic algorithms in development system FUZNET. Finally,
extraction Social, Group and Individual Mind from Multiple Agents
Rule Bases are provided by Cognitive analysis and Matching
criterion.
Abstract: For collecting data from all sensor nodes, some
changes in Dynamic Source Routing (DSR) protocol is proposed. At
each hop level, route-ranking technique is used for distributing
packets to different selected routes dynamically. For calculating rank
of a route, different parameters like: delay, residual energy and
probability of packet loss are used. A hybrid topology of
DMPR(Disjoint Multi Path Routing) and MMPR(Meshed Multi Path
Routing) is formed, where braided topology is used in different
faulty zones of network. For reducing energy consumption, variant
transmission ranges is used instead of fixed transmission range. For
reducing number of packet drop, a fuzzy logic inference scheme is
used to insert different types of delays dynamically. A rule based
system infers membership function strength which is used to
calculate the final delay amount to be inserted into each of the node
at different clusters.
In braided path, a proposed 'Dual Line ACK Link'scheme is
proposed for sending ACK signal from a damaged node or link to a
parent node to ensure that any error in link or any node-failure
message may not be lost anyway. This paper tries to design the
theoretical aspects of a model which may be applied for collecting
data from any large hanging iron structure with the help of wireless
sensor network. But analyzing these data is the subject of material
science and civil structural construction technology, that part is out
of scope of this paper.
Abstract: This paper presents an integrated case based and rule
based reasoning method for car faulty diagnosis. The reasoning
method is done through extracting the past cases from the Proton
Service Center while comparing with the preset rules to deduce a
diagnosis/solution to a car service case. New cases will be stored to
the knowledge base. The test cases examples illustrate the
effectiveness of the proposed integrated reasoning. It has proven
accuracy of similar reasoning if carried out by a service advisor from
the service center.