Abstract: This paper presents a novel two-phase hybrid optimization algorithm with hybrid genetic operators to solve the optimal control problem of a single stage hybrid manufacturing system. The proposed hybrid real coded genetic algorithm (HRCGA) is developed in such a way that a simple real coded GA acts as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method is next employed to do fine tuning. The hybrid genetic operators involved in the proposed algorithm improve both the quality of the solution and convergence speed. The phase–1 uses conventional real coded genetic algorithm (RCGA), while optimisation by direct search and systematic reduction of the size of search region is employed in the phase – 2. A typical numerical example of an optimal control problem with the number of jobs varying from 10 to 50 is included to illustrate the efficacy of the proposed algorithm. Several statistical analyses are done to compare the validity of the proposed algorithm with the conventional RCGA and PSO techniques. Hypothesis t – test and analysis of variance (ANOVA) test are also carried out to validate the effectiveness of the proposed algorithm. The results clearly demonstrate that the proposed algorithm not only improves the quality but also is more efficient in converging to the optimal value faster. They can outperform the conventional real coded GA (RCGA) and the efficient particle swarm optimisation (PSO) algorithm in quality of the optimal solution and also in terms of convergence to the actual optimum value.
Abstract: Biometric techniques are gaining importance for
personal authentication and identification as compared to the
traditional authentication methods. Biometric templates are
vulnerable to variety of attacks due to their inherent nature. When a
person-s biometric is compromised his identity is lost. In contrast to
password, biometric is not revocable. Therefore, providing security
to the stored biometric template is very crucial. Crypto biometric
systems are authentication systems, which blends the idea of
cryptography and biometrics. Fuzzy vault is a proven crypto
biometric construct which is used to secure the biometric templates.
However fuzzy vault suffer from certain limitations like nonrevocability,
cross matching. Security of the fuzzy vault is affected
by the non-uniform nature of the biometric data. Fuzzy vault when
hardened with password overcomes these limitations. Password
provides an additional layer of security and enhances user privacy.
Retina has certain advantages over other biometric traits. Retinal
scans are used in high-end security applications like access control to
areas or rooms in military installations, power plants, and other high
risk security areas. This work applies the idea of fuzzy vault for
retinal biometric template. Multimodal biometric system
performance is well compared to single modal biometric systems.
The proposed multi modal biometric fuzzy vault includes combined
feature points from retina and fingerprint. The combined vault is
hardened with user password for achieving high level of security.
The security of the combined vault is measured using min-entropy.
The proposed password hardened multi biometric fuzzy vault is
robust towards stored biometric template attacks.
Abstract: C-control chart assumes that process nonconformities follow a Poisson distribution. In actuality, however, this Poisson distribution does not always occur. A process control for semiconductor based on a Poisson distribution always underestimates the true average amount of nonconformities and the process variance. Quality is described more accurately if a compound Poisson process is used for process control at this time. A cumulative sum (CUSUM) control chart is much better than a C control chart when a small shift will be detected. This study calculates one-sided CUSUM ARLs using a Markov chain approach to construct a CUSUM control chart with an underlying Poisson-Gamma compound distribution for the failure mechanism. Moreover, an actual data set from a wafer plant is used to demonstrate the operation of the proposed model. The results show that a CUSUM control chart realizes significantly better performance than EWMA.
Abstract: Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.
Abstract: Centrally controlled authentication and authorization services can provide enterprise with an increase in security, more flexible access control solutions and an increased users' trust. By using redirections, users of all Web-based applications within an organization are authenticated at a single well known and secure Web site and using secure communication protocol. Users are first authenticated at the central server using their domain wide credentials before being redirected to a particular Web-based application. The central authentication server will then provide others with pertinence authorization related particulars and credentials of the authenticated user to the specific application. The trust between the clients and the server hosts is established by secure session keys exchange. Case- studies are provided to demonstrate the usefulness and flexibility of the proposed solution.
Abstract: The two-stage compensator designs of linear system are
investigated in the framework of the factorization approach. First, we
give “full feedback" two-stage compensator design. Based on this
result, various types of the two-stage compensator designs with partial
feedbacks are derived.
Abstract: Dengue fever is an important human arboviral disease. Outbreaks are now reported quite often from many parts of the world. The number of cases involving pregnant women and infant cases are increasing every year. The illness is often severe and complications may occur. Deaths often occur because of the difficulties in early diagnosis and in the improper management of the diseases. Dengue antibodies from pregnant women are passed on to infants and this protects the infants from dengue infections. Antibodies from the mother are transferred to the fetus when it is still in the womb. In this study, we formulate a mathematical model to describe the transmission of this disease in pregnant women. The model is formulated by dividing the human population into pregnant women and non-pregnant human (men and non-pregnant women). Each class is subdivided into susceptible (S), infectious (I) and recovered (R) subclasses. We apply standard dynamical analysis to our model. Conditions for the local stability of the equilibrium points are given. The numerical simulations are shown. The bifurcation diagrams of our model are discussed. The control of this disease in pregnant women is discussed in terms of the threshold conditions.
Abstract: This paper describes simple implementation of
homotopy (also called continuation) algorithm for determining the proper resistance of the resistor to dissipate energy at a specified rate of an electric circuit. Homotopy algorithm can be considered as a developing of the classical methods in numerical computing such as Newton-Raphson and fixed
point methods. In homoptopy methods, an embedding
parameter is used to control the convergence. The method purposed in this work utilizes a special homotopy called Newton homotopy. Numerical example solved in MATLAB is given to show the effectiveness of the purposed method
Abstract: Fuzzy logic control (FLC) systems have been tested in
many technical and industrial applications as a useful modeling tool
that can handle the uncertainties and nonlinearities of modern control
systems. The main drawback of the FLC methodologies in the
industrial environment is challenging for selecting the number of
optimum tuning parameters.
In this paper, a method has been proposed for finding the optimum
membership functions of a fuzzy system using particle swarm
optimization (PSO) algorithm. A synthetic algorithm combined from
fuzzy logic control and PSO algorithm is used to design a controller
for a continuous stirred tank reactor (CSTR) with the aim of
achieving the accurate and acceptable desired results. To exhibit the
effectiveness of proposed algorithm, it is used to optimize the
Gaussian membership functions of the fuzzy model of a nonlinear
CSTR system as a case study. It is clearly proved that the optimized
membership functions (MFs) provided better performance than a
fuzzy model for the same system, when the MFs were heuristically
defined.
Abstract: Energy efficient protocol design is the aim of current
researches in the area of sensor networks where limited power
resources impose energy conservation considerations. In this paper
we care for Medium Access Control (MAC) protocols and after an
extensive literature review, two adaptive schemes are discussed. Of
them, adaptive-rate MACs which were introduced for throughput
enhancement show the potency to save energy, even more than
adaptive-power schemes. Then we propose an allocation algorithm
for getting accurate and reliable results. Through a simulation study
we validated our claim and showed the power saving of adaptive-rate
protocols.
Abstract: This paper is concerned with the application of small
rating Capacitive Energy Storage units for the improvement of
Automatic Generation Control of a multiunit multiarea power
system. Generation Rate Constraints are also considered in the
investigations. Integral Squared Error technique is used to obtain the
optimal integral gain settings by minimizing a quadratic performance
index. Simulation studies reveal that with CES units, the deviations
in area frequencies and inter-area tie-power are considerably
improved in terms of peak deviations and settling time as compared
to that obtained without CES units.
Abstract: This paper investigates and compares performance of
various conventional and fuzzy logic based controllers at generator
locations for oscillation damping. Performance of combination of
conventional and fuzzy logic based controllers also studied by
comparing overshoot on the active power deviation response for a
small disturbance and damping ratio of the critical mode. Fuzzy logic
based controllers can not be modeled in the state space form to get
the eigenvalues and corresponding damping ratios of various modes
of generators and controllers. Hence, a new method based on tracing
envelop of time domain waveform is also presented and used in the
paper for comparing performance of controllers. The paper also
shows that if the fuzzy based controllers designed separately
combining them could not lead to a better performance.
Abstract: Thermoelastic temperature, displacement, and
stress in heat transfer during laser surface hardening are solved
in Eulerian formulation. In Eulerian formulations the heat flux
is fixed in space and the workpiece is moved through a control
volume. In the case of uniform velocity and uniform heat flux
distribution, the Eulerian formulations leads to a steady-state
problem, while the Lagrangian formulations remains transient.
In Eulerian formulations the reduction to a steady-state
problem increases the computational efficiency. In this study
also an analytical solution is developed for an uncoupled
transient heat conduction equation in which a plane slab is
heated by a laser beam. The thermal result of the numerical
model is compared with the result of this analytical model.
Comparing the results shows numerical solution for uncoupled
equations are in good agreement with the analytical solution.
Abstract: This paper investigates the problem of designing a robust state-feedback controller for a class of uncertain Markovian jump nonlinear systems that guarantees the L2-gain from an exogenous input to a regulated output is less than or equal to a prescribed value. First, we approximate this class of uncertain Markovian jump nonlinear systems by a class of uncertain Takagi-Sugeno fuzzy models with Markovian jumps. Then, based on an LMI approach, LMI-based sufficient conditions for the uncertain Markovian jump nonlinear systems to have an H performance are derived. An illustrative example is used to illustrate the effectiveness of the proposed design techniques.
Abstract: The paper presents a compressor anti-surge control
system, that results in maximizing compressor throughput with
pressure standard deviation reduction, increased safety margin
between design point and surge limit line and avoiding possible
machine surge. Alternative control strategies are presented.
Abstract: This paper presents a time control liquids mixing
system in the tanks as an application of fuzzy time control discrete
model. The system is designed for a wide range of industrial
applications. The simulation design of control system has three
inputs: volume, viscosity, and selection of product, along with the
three external control adjustments for the system calibration or to
take over the control of the system autonomously in local or
distributed environment. There are four controlling elements: rotatory
motor, grinding motor, heating and cooling units, and valves
selection, each with time frame limit. The system consists of three
controlled variables measurement through its sensing mechanism for
feed back control. This design also facilitates the liquids mixing
system to grind certain materials in tanks and mix with fluids under
required temperature controlled environment to achieve certain
viscous level. Design of: fuzzifier, inference engine, rule base,
deffuzifiers, and discrete event control system, is discussed. Time
control fuzzy rules are formulated, applied and tested using
MATLAB simulation for the system.
Abstract: In this study, we experiment on precise control outlet
temperature of water from the water cooler with hot-gas bypass
method based on PI control logic for machine tool. Recently, technical
trend for machine tools is focused on enhancement of speed and
accuracy. High speedy processing causes thermal and structural
deformation of objects from the machine tools. Water cooler has to be
applied to machine tools to reduce the thermal negative influence with
accurate temperature controlling system. The goal of this study is to
minimize temperature error in steady state. In addition, control period
of an electronic expansion valve were considered to increment of
lifetime of the machine tools and quality of product with a water
cooler.
Abstract: For this study, this researcher conducted a precision
network adjustment with QOCA, the precision network adjustment
software developed by Jet Propulsion Laboratory, to perform an
integrated network adjustment on the Unified Control Points managed
by the National Geographic Information Institute. Towards this end,
275 Unified Control Points observed in 2008 were selected before a
network adjustment is performed on those 275 Unified Control Points.
The RMSE on the discrepancies of coordinates as compared to the
results of GLOBK was ±6.07mm along the N axis, ±2.68mm along the
E axis and ±6.49mm along the U axis.
Abstract: Enhancement of the performance of a reverse osmosis
(RO) unit through periodic control is studied. The periodic control
manipulates the feed pressure and flow rate of the RO unit. To ensure
the periodic behavior of the inputs, the manipulated variables (MV)
are transformed into the form of sinusoidal functions. In this case, the
amplitude and period of the sinusoidal functions become the
surrogate MV and are thus regulated via nonlinear model predictive
control algorithm. The simulation results indicated that the control
system can generate cyclic inputs necessary to enhance the closedloop
performance in the sense of increasing the permeate production
and lowering the salt concentration. The proposed control system can
attain its objective with arbitrary set point for the controlled outputs.
Successful results were also obtained in the presence of modeling
errors.
Abstract: Due to the non-linear characteristics of photovoltaic
(PV) array, PV systems typically are equipped with the capability of
maximum power point tracking (MPPT) feature. Moreover, in the
case of PV array under partially shaded conditions, hotspot problem
will occur which could damage the PV cells. Partial shading causes
multiple peaks in the P-V characteristic curves. This paper presents a
hybrid algorithm of Particle Swarm Optimization (PSO) and
Artificial Neural Network (ANN) MPPT algorithm for the detection
of global peak among the multiple peaks in order to extract the true
maximum energy from PV panel. The PV system consists of PV
array, dc-dc boost converter controlled by the proposed MPPT
algorithm and a resistive load. The system was simulated using
MATLAB/Simulink package. The simulation results show that the
proposed algorithm performs well to detect the true global peak
power. The results of the simulations are analyzed and discussed.