Abstract: In process control applications, above 90% of the
controllers are of PID type. This paper proposed a robust PI
controller with fractional-order integrator. The PI parameters were
obtained using classical Ziegler-Nichols rules but enhanced with the
application of error filter cascaded to the fractional-order PI. The
controller was applied on steam temperature process that was
described by FOPDT transfer function. The process can be classified
as lag dominating process with very small relative dead-time. The
proposed control scheme was compared with other PI controller
tuned using Ziegler-Nichols and AMIGO rules. Other PI controller
with fractional-order integrator known as F-MIGO was also
considered. All the controllers were subjected to set point change and
load disturbance tests. The performance was measured using Integral
of Squared Error (ISE) and Integral of Control Signal (ICO). The
proposed controller produced best performance for all the tests with
the least ISE index.
Abstract: In this paper the neural network-based controller is
designed for motion control of a mobile robot. This paper treats the
problems of trajectory following and posture stabilization of the
mobile robot with nonholonomic constraints. For this purpose the
recurrent neural network with one hidden layer is used. It learns
relationship between linear velocities and error positions of the
mobile robot. This neural network is trained on-line using the
backpropagation optimization algorithm with an adaptive learning
rate. The optimization algorithm is performed at each sample time to
compute the optimal control inputs. The performance of the proposed
system is investigated using a kinematic model of the mobile robot.
Abstract: The objective of this research is parameters optimized
of the stair shape workpiece which is cut by CNC Wire-Cut EDM
(WEDW). The experiment material is SKD-11 steel of stair-shaped
with variable height workpiece 10, 20, 30 and 40 mm. with the same
10 mm. thickness are cut by Sodick's CNC Wire-Cut EDM model
AD325L.
The experiments are designed by 3k full factorial experimental
design at 3 level 2 factors and 9 experiments with 2 replicate. The
selected two factor are servo voltage (SV) and servo feed rate (SF)
and the response is cutting thickness error. The experiment is divided
in two experiments. The first experiment determines the significant
effective factor at confidential interval 95%. The SV factor is the
significant effective factor from first result. In order to result smallest
cutting thickness error of workpieces is 17 micron with the SV value
is 46 volt. Also show that the lower SV value, the smaller different
thickness error of workpiece. Then the second experiment is done to
reduce different cutting thickness error of workpiece as small as
possible by lower SV. The second experiment result show the
significant effective factor at confidential interval 95% is the SV
factor and the smallest cutting thickness error of workpieces reduce
to 11 micron with the experiment SV value is 36 volt.
Abstract: The aim of this study is to develop a cost-effective WBGT heat stress monitor which provides precise heat stress measurement. The proposed device employs SHT15 and DS18B20 as a temperature and humidity sensors, respectively, incorporating with ATmega328 microcontroller. The developed heat stress monitor was calibrated and adjusted to that of the standard temperature and humidity sensors in the laboratory. The results of this study illustrated that the mean percentage error and the standard deviation from the measurement of the globe temperature was 2.33 and 2.71 respectively, while 0.94 and 1.02 were those of the dry bulb temperature, 0.79 and 0.48 were of the wet bulb temperature, and 4.46 and 1.60 were of the relative humidity sensor. This device is relatively low-cost and the measurement error is acceptable.
Abstract: The exhaustive quality control is becoming more and
more important when commercializing competitive products in the
world's globalized market. Taken this affirmation as an undeniable
truth, it becomes critical in certain sector markets that need to offer
the highest restrictions in quality terms. One of these examples is the
percussion cap mass production, a critical element assembled in
firearm ammunition. These elements, built in great quantities at a
very high speed, must achieve a minimum tolerance deviation in
their fabrication, due to their vital importance in firing the piece of
ammunition where they are built in. This paper outlines a machine
vision development for the 100% inspection of percussion caps
obtaining data from 2D and 3D simultaneous images. The acquisition
speed and precision of these images from a metallic reflective piece
as a percussion cap, the accuracy of the measures taken from these
images and the multiple fabrication errors detected make the main
findings of this work.
Abstract: This research presents a fuzzy multi-objective model
for a machine selection problem in a flexible manufacturing system
of a tire company. Two main objectives are minimization of an
average machine error and minimization of the total setup time.
Conventionally, the working team uses trial and error in selecting a
pressing machine for each task due to the complexity and constraints
of the problem. So, both objectives may not satisfy. Moreover, trial
and error takes a lot of time to get the final decision. Therefore, in
this research preemptive fuzzy goal programming model is developed
for solving this multi-objective problem. The proposed model can
obtain the appropriate results that the Decision Making (DM) is
satisfied for both objectives. Besides, alternative choice can be easily
generated by varying the satisfaction level. Additionally, decision
time can be reduced by using the model, which includes all
constraints of the system to generate the solutions. A numerical
example is also illustrated to show the effectiveness of the proposed
model.
Abstract: This paper proposes, for the first time, how the
challenges facing the guard-band designs including the margin
assist-circuits scheme for the screening-test in the coming process
generations should be addressed. The increased screening error
impacts are discussed based on the proposed statistical analysis
models. It has been shown that the yield-loss caused by the
misjudgment on the screening test would become 5-orders of
magnitude larger than that for the conventional one when the
amplitude of random telegraph noise (RTN) caused variations
approaches to that of random dopant fluctuation. Three fitting methods
to approximate the RTN caused complex Gamma mixtures
distributions by the simple Gaussian mixtures model (GMM) are
proposed and compared. It has been verified that the proposed
methods can reduce the error of the fail-bit predictions by 4-orders of
magnitude.
Abstract: The modern world is experiencing fundamental and dynamic changes. The transformation of international relations; the end of confrontation and successive overcoming of the Cold War consequences have expanded possible international cooperation. The global nuclear conflict threat has been minimized, while a tendency to establish a unipolar world structure with the U.S. economic and power domination is growing. The current world system of international relations, apparently is secular. However, the religious beliefs of one or another nations play a certain (sometimes a key) role, both in the domestic affairs of the individual countries and in the development of bilateral ties. Political situation in Central Asia has been characterized by new factors such as international terrorism; religious extremism and radicalism; narcotrafficking and illicit arms trade of a global character immediately threaten to peace and political stability in Central Asia. The role and influence of Islamic fundamentalism is increasing; political ethnocentrism and the associated aggravation of inter-ethnic relations, the ambiguity of national interests and objectives of major geo-political groups in the Central Asian region regarding the division the political influence, emerge. This article approaches the following issues: the role of Islam in Central Asia; destabilizing factors in Central Asia; Islamic movements in Central Asia, Western Europe and the United States; the United States, Western Europe and Central Asia: religion, politics, ideology, and the US-Central Asia antiterrorism and religious extremism cooperation.
Abstract: The optimal design of PI controller for Automatic Generation Control in two area is presented in this paper. The concept of Dual mode control is applied in the PI controller, such that the proportional mode is made active when the rate of change of the error is sufficiently larger than a specified limit otherwise switched to the integral mode. A digital simulation is used in conjunction with the Hooke-Jeeve’s optimization technique to determine the optimum parameters (individual gain of proportional and integral controller) of the PI controller. Integrated Square of the Error (ISE), Integrated Time multiplied by Absolute Error(ITAE) , and Integrated Absolute Error(IAE) performance indices are considered to measure the appropriateness of the designed controller. The proposed controller are tested for a two area single nonreheat thermal system considering the practical aspect of the problem such as Deadband and Generation Rate Constraint(GRC). Simulation results show that dual mode with optimized values of the gains improved the control performance than the commonly used Variable Structure .
Abstract: The authors present an optimization algorithm for order reduction and its application for the determination of the relative mapping errors of linear time invariant dynamic systems by the simplified models. These relative mapping errors are expressed by means of the relative integral square error criterion, which are determined for both unit step and impulse inputs. The reduction algorithm is based on minimization of the integral square error by particle swarm optimization technique pertaining to a unit step input. The algorithm is simple and computer oriented. It is shown that the algorithm has several advantages, e.g. the reduced order models retain the steady-state value and stability of the original system. Two numerical examples are solved to illustrate the superiority of the algorithm over some existing methods.
Abstract: Recent scientific investigations indicate that
multimodal biometrics overcome the technical limitations of
unimodal biometrics, making them ideally suited for everyday life
applications that require a reliable authentication system. However,
for a successful adoption of multimodal biometrics, such systems
would require large heterogeneous datasets with complex multimodal
fusion and privacy schemes spanning various distributed
environments. From experimental investigations of current
multimodal systems, this paper reports the various issues related to
speed, error-recovery and privacy that impede the diffusion of such
systems in real-life. This calls for a robust mechanism that caters to
the desired real-time performance, robust fusion schemes,
interoperability and adaptable privacy policies.
The main objective of this paper is to present a framework that
addresses the abovementioned issues by leveraging on the
heterogeneous resource sharing capacities of Grid services and the
efficient machine learning capabilities of artificial neural networks
(ANN). Hence, this paper proposes a Grid-based neural network
framework for adopting multimodal biometrics with the view of
overcoming the barriers of performance, privacy and risk issues that
are associated with shared heterogeneous multimodal data centres.
The framework combines the concept of Grid services for reliable
brokering and privacy policy management of shared biometric
resources along with a momentum back propagation ANN (MBPANN)
model of machine learning for efficient multimodal fusion and
authentication schemes. Real-life applications would be able to adopt
the proposed framework to cater to the varying business requirements
and user privacies for a successful diffusion of multimodal
biometrics in various day-to-day transactions.
Abstract: In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade
Abstract: A multi fingered dexterous anthropomorphic hand is
being developed by the authors. The focus of the hand is the
replacement of human operators in hazardous environments and also
in environments where zero tolerance is observed for the human
errors. The robotic hand will comprise of five fingers (four fingers
and one thumb) each having four degrees of freedom (DOF) which
can perform flexion, extension, abduction, adduction and also
circumduction. For the actuation purpose pneumatic muscles and
springs will be used. The paper exemplifies the mechanical design for
the robotic hand. It also describes different mechanical designs that
have been developed before date.
Abstract: In this research, the researchers have managed to
design a model to investigate the current trend of stock price of the
"IRAN KHODRO corporation" at Tehran Stock Exchange by
utilizing an Adaptive Neuro - Fuzzy Inference system. For the Longterm
Period, a Neuro-Fuzzy with two Triangular membership
functions and four independent Variables including trade volume,
Dividend Per Share (DPS), Price to Earning Ratio (P/E), and also
closing Price and Stock Price fluctuation as an dependent variable are
selected as an optimal model. For the short-term Period, a neureo –
fuzzy model with two triangular membership functions for the first
quarter of a year, two trapezoidal membership functions for the
Second quarter of a year, two Gaussian combination membership
functions for the third quarter of a year and two trapezoidal
membership functions for the fourth quarter of a year were selected
as an optimal model for the stock price forecasting. In addition, three
independent variables including trade volume, price to earning ratio,
closing Stock Price and a dependent variable of stock price
fluctuation were selected as an optimal model. The findings of the
research demonstrate that the trend of stock price could be forecasted
with the lower level of error.
Abstract: Let T and S be a subspace of Cn and Cm, respectively.
Then for A ∈ Cm×n satisfied AT ⊕ S = Cm, the generalized
inverse A(2)
T,S is given by A(2)
T,S = (PS⊥APT )†. In this paper, a
finite formulae is presented to compute generalized inverse A(2)
T,S
under the concept of restricted inner product, which defined as <
A,B >T,S=< PS⊥APT,B > for the A,B ∈ Cm×n. By this
iterative method, when taken the initial matrix X0 = PTA∗PS⊥, the
generalized inverse A(2)
T,S can be obtained within at most mn iteration
steps in absence of roundoff errors. Finally given numerical example
is shown that the iterative formulae is quite efficient.
Abstract: Government spending is categorized into consumption spending and capital spending. Three categories of private consumption are used: food consumption, nonfood consumption, and services consumption. The estimated model indicates substitution effects of government consumption spending on budget shares of private nonfood consumption and of government capital spending on budget share of private food consumption. However, the results do not indicate whether the negative effects of changes in the budget shares of the nonfood and the food consumption equates to reduce total private consumption. The concept of aggregate demand comprising consumption, investment, government spending (consumption spending and capital spending), export, and import are used to estimate their relationship by using the Vector Error Correction Mechanism. The study found no effect of government capital spending on either the private consumption or the growth of GDP while the government consumption spending has negative effect on the growth of GDP.
Abstract: In this paper, a new time discontinuous expanded mixed finite element method is proposed and analyzed for two-order convection-dominated diffusion problem. The proofs of the stability of the proposed scheme and the uniqueness of the discrete solution are given. Moreover, the error estimates of the scalar unknown, its gradient and its flux in the L1( ¯ J,L2( )-norm are obtained.
Abstract: This paper investigates the performance of Multiple- Input Multiple-Output (MIMO) feedback system combined with Orthogonal Frequency Division Multiplexing (OFDM). Two types of codebook based channel feedback techniques are used in this work. The first feedback technique uses a combination of both the long-term and short-term channel state information (CSI) at the transmitter, whereas the second technique uses only the short term CSI. The long-term and short-term CSI at the transmitter is used for efficient channel utilization. OFDM is a powerful technique employed in communication systems suffering from frequency selectivity. Combined with multiple antennas at the transmitter and receiver, OFDM proves to be robust against delay spread. Moreover, it leads to significant data rates with improved bit error performance over links having only a single antenna at both the transmitter and receiver. The effectiveness of these techniques has been demonstrated through the simulation of a MIMO-OFDM feedback system. The results have been evaluated for 4x4 MIMO channels. Simulation results indicate the benefits of the MIMO-OFDM channel feedback system over the one without incorporating OFDM. Performance gain of about 3 dB is observed for MIMO-OFDM feedback system as compared to the one without employing OFDM. Hence MIMO-OFDM becomes an attractive approach for future high speed wireless communication systems.
Abstract: This paper presents an analysis of the localization accuracy of indoor positioning systems using Cramer-s rule via IEEE 802.15.4 wireless sensor networks. The objective is to study the impact of the methods used to convert the received signal strength into the distance that is used to compute the object location in the wireless indoor positioning system. Various methods were tested and the localization accuracy was analyzed. The experimental results show that the method based on the empirical data measured in the non line-of-sight (NLOS) environment yield the highest localization accuracy; with the minimum error distance less than 3 m.
Abstract: In this paper, a residue number arithmetic is used in
direct sequence spread spectrum system, this system is evaluated and
the bit error probability of this system is compared to that of non
residue number system. The effect of channel bandwidth, PN
sequences, multipath effect and modulation scheme are studied. A
Matlab program is developed to measure the signal-to-noise ratio
(SNR), and the bit error probability for the various schemes.