IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING

This work is intended to design a new robust load-frequency controller for Iraqi NationalSuper Grid System with uncertain parameters. Riccati equation approach to thestabilization of uncertain system is proposed. Robust controller that ensures stability of theclosed-loop system for all admissible structured uncertainties is designed. ‘Matchingconditions’ and Lyapunov stability theory are used to implement a robust stabilizingcontroller. Participation factor used to address the interaction between the state variablesand the modes in the power system. This property is used to choose weighting matrix of thestate variables (Q). A linear, time, invariant mathematical model is derived for IraqiNational Super Grid System consisting of six generating stations with various types ofturbines. The proposed approach is applied on this system and simulation program is builtto evaluate its effectiveness.

Industrial Ethernet is a new trend in technology designed to replace the traditionalindustrial solutions such as point to point and field bus systems. This paper studiesIndustrial Ethernet performance under different circumstances using the network simulationpackage(OPNET). Firstly, a validation procedure to the use of OPNET in simulating suchnetworks was made by comparing OPNET performance with practical experiments onceand then with analytical models results. Then OPNET was used to study the effect ofdifferent parameters on the real time performance of the network. It was found that someparameters like (packet length, number of nodes and packet production rate) have minoreffect on the network performance, while the others (packets processing rate and FTPtraffic transferred to an industrial node) could affect seriously on the network behavior.Keywords: Industrial Ethernet , OPNET , Field bus , TCP/IP

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.

Most of the positioning technologies for modern inertial navigation systems have beenavailable for the last 25 years that has focused on development of the Strap-down InertialNavigation Systems (SINS) because of its low cost.This paper presents an intelligent navigator to overcome the limitations of existing SINSalgorithms. This algorithm is based on Artificial Neural Network (ANN).Using window based weight updating strategy; the intelligent navigator was evaluated usingseveral SINS hypothetical field tests data and the results demonstrated superior performance totraditional navigator in the position domain.

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.

In this paper, an indirect field-oriented control (IFOC) induction machine drivewith a conventional PI and sliding mode controllers is presented. The robustness of acmachine drive speed performance with these controllers is checked in terms of variationof machine parameters.The design includes rotor speed estimation from measured stator terminalvoltages and currents. The estimated speed is used as feedback in an indirect vectorcontrol system, such that the speed control is performed without the use of shaftmounted transducers.The high performance of the proposed control schemes under load disturbancesis studied via simulation cases. The components of the speed controlled indirect field-orientedinduction machine with the both controllers are simulated using SIMULINK,while the dynamic of induction machine is simulated using the potential of S-functionblock and its attached script file.

Image identification plays a great role in industrial, remote sensing, and militaryapplications. 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 imagedepending on the distribution of the monochrome colors (red, green, and blue) in the sameimage to make image signature accordingly, which is represented by a values named powerspectrum. The first step is to analyze the three-band monochrome image (color image) toRed, Green and Blue image, then deal with each image as a grey scale one which isrepresented as a 2-D matrix. The second step is to make Fourier Transform to each greyscale 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 foreach one. Finally, in the third step, and in order to handle problems of large inputdimensions, 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 obtainedfrom the previous step. All programs are written using MATLAP VER. 6.5 programminglanguage.

A combination of fuzzy logic and neural network can generate a fuzzy neuralcontroller which in association with a neural network emulator can improve the outputresponse of the controlled system. This combination uses the neural network trainingability to adjust the membership functions of a PID like fuzzy neural controller. Suchcontroller can be used to adaptively control nonlinear MIMO systems.The goal of the controller is to force the controlled system to follow a referencemodel with required transient specifications of minimum overshoot, minimum rise timeand minimum steady state error. The fuzzy membership functions were tuned using thepropagated error between the plant outputs and the desired ones.To propagate the error from the plant outputs to the controller, a neural networkis used as a channel to the error. This neural network uses the back propagationalgorithm as a learning technique.The controller was tested using two inputs / two outputs nonlinear time invariantmodel. 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.

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.

Digital images are widely used in computer applications. Uncompressed digitalimages require considerable storage capacity and transmission bandwidth. Efficient imagecompression solutions are becoming more critical with the recent growth of data intensiveand multimedia-based web application.In this paper, Hybrid Differential Pulse Code Modulation (DPCM) in waveletdomain and lossless methods (Huffman and Run length code) for image compression isinvestigated. The image signal is composed into four scales (approximate, horizontal,vertical and diagonal coefficients). The energy level of approximate is different from that ofdetail information; therefore, the approximate is quantized alone and horizontal and verticalare quantized alone by using the differential pulse code modulation (DPCM). In allsimulations the diagonal coefficients are discarded. Two types of coding are used, Huffmancode and run length coding (RLC) techniques. The results show that truncate horizontaland vertical coefficients using hard threshold gives best performance than soft thresholdwith gain about 3 dB to get the same compression ratio (CR). The wavelet based imagecompression using Huffman code gives CR about 77% compared with RLC that gives CRabout 71% with suitable peak signal to noise ratio (PSNR).Key words: image compression, discrete wavelet transforms (DWT), differential pulsecode modulation (DPCM), Huffman code and run length code (RLC)