Lokman H. Hassan Al-Sharafany; Dr. Rashid H. Al-Rubayi
Volume 7, Issue 1 , June 2007, Page 1-20
Abstract
Abstract:
This work is intended to design a new robust load-frequency controller for Iraqi National
Super Grid System with uncertain parameters. Riccati equation approach to the
stabilization of uncertain system is proposed. Robust controller that ensures stability of the
closed-loop system for all ...
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Abstract:
This work is intended to design a new robust load-frequency controller for Iraqi National
Super Grid System with uncertain parameters. Riccati equation approach to the
stabilization of uncertain system is proposed. Robust controller that ensures stability of the
closed-loop system for all admissible structured uncertainties is designed. ‘Matching
conditions’ and Lyapunov stability theory are used to implement a robust stabilizing
controller. Participation factor used to address the interaction between the state variables
and the modes in the power system. This property is used to choose weighting matrix of the
state variables (Q). A linear, time, invariant mathematical model is derived for Iraqi
National Super Grid System consisting of six generating stations with various types of
turbines. The proposed approach is applied on this system and simulation program is built
to evaluate its effectiveness.
Dr.Basil Sh. Mahmood; Qutiaba Ibrahem Ali
Volume 7, Issue 1 , June 2007, Page 21-30
Abstract
Abstract:
Industrial Ethernet is a new trend in technology designed to replace the traditional
industrial solutions such as point to point and field bus systems. This paper studies
Industrial Ethernet performance under different circumstances using the network simulation
package(OPNET). Firstly, ...
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Abstract:
Industrial Ethernet is a new trend in technology designed to replace the traditional
industrial solutions such as point to point and field bus systems. This paper studies
Industrial Ethernet performance under different circumstances using the network simulation
package(OPNET). Firstly, a validation procedure to the use of OPNET in simulating such
networks was made by comparing OPNET performance with practical experiments once
and then with analytical models results. Then OPNET was used to study the effect of
different parameters on the real time performance of the network. It was found that some
parameters like (packet length, number of nodes and packet production rate) have minor
effect on the network performance, while the others (packets processing rate and FTP
traffic transferred to an industrial node) could affect seriously on the network behavior.
Keywords: Industrial Ethernet , OPNET , Field bus , TCP/IP
Nabeel E. Adam
Volume 7, Issue 1 , June 2007, Page 31-40
Abstract
Abstract:
The input voltage to the direct current series motor is controlled by means of an optimal regulator, for changing the firing angle of the thyristors using pulse width modulation technique. An input output linearization technique is introduced to linearize the non–linear mathematical model ...
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Abstract:
The input voltage to the direct current series motor is controlled by means of an optimal regulator, for changing the firing angle of the thyristors using pulse width modulation technique. An input output linearization technique is introduced to linearize the non–linear mathematical model of the d.c series motor system .The open-loop and closed-loop control systems hve been analyzed theoretically. A computer program written in a MATLAB is used for computing the system dynamics. The closed-loop control system shows a significant modification in the system parameters like armature current,peak overshoot,settling time……..etc,and an optimal firing angle is achieved.
Dr. Salam A. Ismaeel
Volume 7, Issue 1 , June 2007, Page 41-49
Abstract
Abstract:
Most of the positioning technologies for modern inertial navigation systems have been
available for the last 25 years that has focused on development of the Strap-down Inertial
Navigation Systems (SINS) because of its low cost.
This paper presents an intelligent navigator to overcome the ...
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Abstract:
Most of the positioning technologies for modern inertial navigation systems have been
available for the last 25 years that has focused on development of the Strap-down Inertial
Navigation Systems (SINS) because of its low cost.
This paper presents an intelligent navigator to overcome the limitations of existing SINS
algorithms. This algorithm is based on Artificial Neural Network (ANN).
Using window based weight updating strategy; the intelligent navigator was evaluated using
several SINS hypothetical field tests data and the results demonstrated superior performance to
traditional navigator in the position domain.
Prof. Maher K. Al-Azawi; Mohanad E. Al-Madi
Volume 7, Issue 1 , June 2007, Page 50-61
Abstract
Abstract :
The effectiveness of Orthogonal Frequency Division Multiplexing (OFDM) with π//4-DQPSK modulation is investigated, for communication over HF channel. The Fast Fourier Transform (FFT) is used to satisfy the orthogonality between subcarriers and reduce the implementation complexity. The system ...
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Abstract :
The effectiveness of Orthogonal Frequency Division Multiplexing (OFDM) with π//4-DQPSK modulation is investigated, for communication over HF channel. The Fast Fourier Transform (FFT) is used to satisfy the orthogonality between subcarriers and reduce the implementation complexity. The system performance is investigated for various delay spreads, coherence time and number of propagation paths. A guard time with cyclic extension is used to reduce channel dispersion, intersymbol and intercarrier interference. Clipping is used to minimize the high peak-to-average power (PAP) ratio.
Dr. Noaman M. Noaman
Volume 7, Issue 1 , June 2007, Page 62-73
Abstract
Abstract
In this paper, an indirect field-oriented control (IFOC) induction machine drive
with a conventional PI and sliding mode controllers is presented. The robustness of ac
machine drive speed performance with these controllers is checked in terms of variation
of machine parameters.
The design ...
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Abstract
In this paper, an indirect field-oriented control (IFOC) induction machine drive
with a conventional PI and sliding mode controllers is presented. The robustness of ac
machine drive speed performance with these controllers is checked in terms of variation
of machine parameters.
The design includes rotor speed estimation from measured stator terminal
voltages and currents. The estimated speed is used as feedback in an indirect vector
control system, such that the speed control is performed without the use of shaft
mounted transducers.
The high performance of the proposed control schemes under load disturbances
is studied via simulation cases. The components of the speed controlled indirect field-oriented
induction machine with the both controllers are simulated using SIMULINK,
while the dynamic of induction machine is simulated using the potential of S-function
block and its attached script file.
M.Sc. Hassan J. Hassan
Volume 7, Issue 1 , June 2007, Page 74-86
Abstract
Abstract:
Image identification plays a great role in industrial, remote sensing, and military
applications. It is concerned with the generation of a signature to the image.
This work proposes a dynamic program (use Neural Network) to identify the color image
depending on the distribution of the monochrome ...
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Abstract:
Image identification plays a great role in industrial, remote sensing, and military
applications. It is concerned with the generation of a signature to the image.
This work proposes a dynamic program (use Neural Network) to identify the color image
depending on the distribution of the monochrome colors (red, green, and blue) in the same
image to make image signature accordingly, which is represented by a values named power
spectrum. The first step is to analyze the three-band monochrome image (color image) to
Red, Green and Blue image, then deal with each image as a grey scale one which is
represented as a 2-D matrix. The second step is to make Fourier Transform to each grey
scale image in order to extract the implicit information in that image. The calculations of 2-
D Power Spectrum for each image have been done to construct the final feature vector for
each one. Finally, in the third step, and in order to handle problems of large input
dimensions, a multilayer perceptron Neural Network has been used with two hidden layers.
The input of the Neural Network structure is the final feature vectors which are obtained
from the previous step. All programs are written using MATLAP VER. 6.5 programming
language.
Mr. Qussay F. Ad; Doory; Dr. Mohammed Yousif Hassan
Volume 7, Issue 1 , June 2007, Page 87-96
Abstract
Abstract:
A combination of fuzzy logic and neural network can generate a fuzzy neural
controller which in association with a neural network emulator can improve the output
response of the controlled system. This combination uses the neural network training
ability to adjust the membership functions ...
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Abstract:
A combination of fuzzy logic and neural network can generate a fuzzy neural
controller which in association with a neural network emulator can improve the output
response of the controlled system. This combination uses the neural network training
ability to adjust the membership functions of a PID like fuzzy neural controller. Such
controller can be used to adaptively control nonlinear MIMO systems.
The goal of the controller is to force the controlled system to follow a reference
model with required transient specifications of minimum overshoot, minimum rise time
and minimum steady state error. The fuzzy membership functions were tuned using the
propagated error between the plant outputs and the desired ones.
To propagate the error from the plant outputs to the controller, a neural network
is used as a channel to the error. This neural network uses the back propagation
algorithm as a learning technique.
The controller was tested using two inputs / two outputs nonlinear time invariant
model. Different reference (set-point) inputs were applied to the closed loop system.
Also, different values of loads and disturbances were applied to the closed loop system.
Simulation results show that the controller achieves the design requirements.
Ms.c. Hussain Karrem Khleaf; Assit. Prof. Dr. Hanan A. R. Akkar
Volume 7, Issue 1 , June 2007, Page 97-110
Abstract
ABSTRACT:
In this paper back-propagation neural network is presented for pattern recognition of ECG wave analysis and diagnosis, where training is applied for some common heart disease. Linear Predictive Coding (LPC) is used as a proposed method to compress the data, which were extracted from electrocardiogram, ...
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ABSTRACT:
In this paper back-propagation neural network is presented for pattern recognition of ECG wave analysis and diagnosis, where training is applied for some common heart disease. Linear Predictive Coding (LPC) is used as a proposed method to compress the data, which were extracted from electrocardiogram, ECG paper. LPC method is tested before using it in this work, where it has succeeded in verifying coding operation to the signals. This method is efficient to reduce the ANN size used in this work. Data used are obtained from all currently available ECG databases, which were previously collected from different fields, such as Internet sites, different hospitals and some publications related with this field. The ECG samples were processed and normalized to produce a set of data that was applied to LPC and then to Artificial Neural Network (ANN). The results obtained are compared with the classifications made by a Doctor, where these results proved an efficient diagnosis with good performance and accuracy. Simulation results are obtained using technical (MATLAB) package implemented on IBM PC.
Fadel S. Hassen; Ahmed K. Hassan
Volume 7, Issue 1 , June 2007, Page 111-124
Abstract
Abstract:
Digital images are widely used in computer applications. Uncompressed digital
images require considerable storage capacity and transmission bandwidth. Efficient image
compression solutions are becoming more critical with the recent growth of data intensive
and multimedia-based web application.
In ...
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Abstract:
Digital images are widely used in computer applications. Uncompressed digital
images require considerable storage capacity and transmission bandwidth. Efficient image
compression solutions are becoming more critical with the recent growth of data intensive
and multimedia-based web application.
In this paper, Hybrid Differential Pulse Code Modulation (DPCM) in wavelet
domain and lossless methods (Huffman and Run length code) for image compression is
investigated. The image signal is composed into four scales (approximate, horizontal,
vertical and diagonal coefficients). The energy level of approximate is different from that of
detail information; therefore, the approximate is quantized alone and horizontal and vertical
are quantized alone by using the differential pulse code modulation (DPCM). In all
simulations the diagonal coefficients are discarded. Two types of coding are used, Huffman
code and run length coding (RLC) techniques. The results show that truncate horizontal
and vertical coefficients using hard threshold gives best performance than soft threshold
with gain about 3 dB to get the same compression ratio (CR). The wavelet based image
compression using Huffman code gives CR about 77% compared with RLC that gives CR
about 71% with suitable peak signal to noise ratio (PSNR).
Key words: image compression, discrete wavelet transforms (DWT), differential pulse
code modulation (DPCM), Huffman code and run length code (RLC)