Print ISSN: 1811-9212

Online ISSN: 2617-3352

Issue 3,

Issue 3


Design of an Auto-Tuning PID Controller for Systems based on Slice Genetic Algorithm

Khulood E. Dagher

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2013, Volume 13, Issue 3, Pages 1-9

Abstract – This paper introduces the Slice Genetics Algorithm SGA which represents
the proposed modification to the classic Genetic Algorithm GA scheme. The proposed
algorithm has reduced the population size and maximum iteration in order to get fast
and an optimal solution. This algorithm has been used for determining the optimal
proportional- integral- derivative PID controller parameters. The proposed algorithm
has versatile features, including, fast, stable rate convergence characteristic also it has
good computational efficiency in improving the dynamic behavior for the system in
term of reducing the maximum overshoot, rise time, settling time and steady-states
error. The algorithm not only has benefit to improve the convergence characteristic,
accuracy but it also shortened the processing time towards the optimal value based
reducing the number of iteration from 40 to 4 or 6 iteration as clear in the MATLAB
simulation results..

Multispectral Fusion for Synthetic Aperture Radar (SAR) Image Based Framelet Transform

Mohammed Hussein Miry

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2013, Volume 13, Issue 3, Pages 10-14

Abstract-The technique of fusing a panchromatic (Pan) SAR image that has a highspatial
and low-spectral resolution with multispectral (MS) SAR images that have a
low-spatial and high spectral resolution is very useful in many remote sensing
applications that require both high-spatial and high-spectral resolution. In this paper,
method for fusion SAR image is proposed based on framelet transform and new
selection rule. The framelet transform is nearly shift-invariant with desired properties,
short support, and symmetry. In the selection rule of proposed method, max rule is
replaced with new relation depending on input SAR image. The proposed method is
compared with other method such as HIS, PCA and wavelet methods. A quality of fused
image is calculated based on the combination entropy, the correlation coefficient and
the peak signal to noise ratio. It is showed from simulation result the quality measured
for proposed method can indicate the information content of the fused image is higher
compared to the information content of the input panchromatic and multispectral
images, also its noticed the proposed method provides richer information comparing
with other methods.

Design of a Direct Neural Braking System based on Switching Gains Controller

Dr. Hayder Sabah. Abdulamir

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2013, Volume 13, Issue 3, Pages 15-26

Abstract- In this paper, direct neural controller for braking system is proposed.
Learning of the presented controller depends on the training data that comes from
running the switching gain controller at different conditions of drive. The training data
consist of relative velocity error, distance error and braking force. The feed-forward
neural network is used to build direct neural controller with two hidden layers and using
back-propagation training algorithm. The performance of the presented controller is
validated using nonlinear braking model. Simulation results show the presented
controller is able to prevent the collision of vehicles at different driving conditions.
Also, the results show superiority of the direct neural controller in comparison with the
switching gain controller at all drive cases that are tested in this work.

Solving Categorization Problem using Two Models of Machine Learning

Lubna Zaghlul Bashir; Nada Mahdi

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2013, Volume 13, Issue 3, Pages 27-40

Abstract-The ability to recognize quickly and accurately which we encounter is
fundamental to normal intelligent human behavior. However, how the learning of
categories which objects in the world fit into takes place is still an unanswered question.
One thing is certain though; much of the learning that takes place allows humans to
cope with the changing they encounter. One of the most important aspects of human
intelligence is its flexibility which has allowed humans to prosper in a dynamic world.
Humans do not suffer from the ills of old fashioned hard rule based artificial
intelligence. The study tested six cubes. The vertices of the cubes represent individual
stimuli constructed from three binary dimensions. The dimension of the stimuli can be
assumed to correspond to shape (square vs. circle), color (black vs. white), and size
(large vs. small). Four stimuli belonged to one category and the other four to a different
category. These constraints result in six problem types, which are illustrated by the six
cubes. The circle vertices represent stimuli that belong to category A, and the square
vertices represent stimuli that belong to category B. The faces of the cubes represent a
constant value across one of the three dimensions that define the stimuli. This work
presents experiments with two different classifier systems: learning when fitness is
based upon strength and specificity, and learning when fitness is based on strength
alone. The system is implemented using Pascal programming language. Results show
lower performance of the system when depending on strength alone. By contrast, the
run with strength and specificity allows a fast desired output.

High-Pass Digital Filter Implementation Using FPGA

Dr. Manal H. Jassim; Asaad Hameed Sahar

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2013, Volume 13, Issue 3, Pages 41-50

Abstract-Depending on the response of the system, digital Filters can be designed
using frequency sampling or windowing methods; but these methods have a problem in
precise control of the critical frequencies. In the sampling method, the weighted
approximation error between the actual frequency response and the desired filter
response is spread across the pass-band and the stop-band and the maximum error is
minimized, resulting ripples in the pass-band and the stop-band. The frequency
sampling method has the same tolerance requirements as the windowing method. In this
work we implemented a digital FIR high pass filter using MATLAB program
(FDATools) using sampling and windowing methods, then the design in the FPGA kit
is downloaded by generating VHDL description. A comparison the amount of the
component has been used in the FPGA for both methods. The FIR filter is implemented
using Spartan 3AN- XC3S700a-4FG484FPGA and simulated with the help of Xilinx
ISE (Integrated Software Environment) Software WEBPACK Project Navigator 11i.

Study the Robustness of Automatic Voltage Regulator for Synchronous Generator Based on Neural Network

Dr. Abdulrahim Thiab Humod

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2013, Volume 13, Issue 3, Pages 51-64

Abstract – Artificial Neural Networks (ANN) can be used as intelligent controllers to
control non-linear dynamic systems through learning, which can easily accommodate
the non linearity’s, time dependencies, model uncertainty and external disturbances.
Modern power systems are complex and non-linear and their operating conditions can
vary over a wide range. The Nonlinear Auto-Regressive Moving Average (NARMAL2)
model system is proposed as an effective neural networks controller model to
achieve the desired robust Automatic Voltage Regulator (AVR) for Synchronous
Generator (SG) to maintain constant terminal voltage. The concerned neural networks
controller for AVR is examined on different models of SG and loads. The results shows
that the neuro-controllers have excellent responses for all SG models and loads in view
point of transient response and system stability compared with conventional PID
controllers. Also shows that the margins of robustness for neuro-controller are greater
than PID controller.

Rule Induction Technique for Fingerprint Identification

Awad Kadhim Hammoud; Hattam Nahi Muhaisen

IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2013, Volume 13, Issue 3, Pages 65-72

Abstract – Pattern recognition problems computer based are very important and
essential in our real life. There are many approaches have been used in pattern
recognition problem such as: Fourier Descriptor, Moment Invariant. But the main defect
of these methods is the long time processing and large computer space. This paper,
presents a new approach Artificial Intelligence, of Rule Induction technique. By this
approach, the essential and specific features of object have been extracted from contour
of object to be recognized. The characteristic of these features are easy computed and
requires fewer amounts of time and space, then high speed in recognition and decision.
Such features are (number of curves inside the fingerprint, number of check point for
each curve). It gives good and accurate results. We test the performance of this system
using many contours of fingerprint, and get good and accurate results.