Majlesi Journal of Electrical Engineering
Volume:3 Issue: 3, 2009

In this paper the robust control of multi variable singular perturbation systems is studied. In order to robust the control of the system, only the additive modeling error is considered. Based on the above bounds of modeling error and the Nyquist criteria and in order to improve the performance of the system a relation is found to determine the robust controller. The singular perturbation system is decomposed into fast and slow subsystems and the robust controller is designed for reduced order systems. It is explained how to find the new bound to stabilize the system and decrease the sensitivity.

In this paper, the characteristics of photonic crystal fibers (PCFs), which have been experimentally determined in the last few years in Iran's Telecom Research Center are analyzed and compared theoretically using an effective index method. The PCFs under investigation are fabricated with a high speed drawing process that has not yet been reported elsewhere. It was shown that at higher wavelengths in PCFs; the light field is confined in the core where in shorter wavelengths the field spreads into the cladding region. This phenomenon leads to affect the numerical aperture and the normalized frequency of the PCFs, because these two parameters directly depend on the diameter of the air-hole and the spacing between them in the cladding region. The measured results show that the PCF fabricated at high drawing speeds has a loss of 12 dB/km of speed, which is a reasonable level compared to other published reports. In addition, we have shown that a lower spacing between the adjacent air-holes would reduce the loss in the PCFs.

This paper presents a simple watermarking approach based on the rotation of low frequency components in image blocks. The rotation process is performed with less distortion by projecting the samples on specific lines according to their message bit. To optimize the detection, the Maximum Likelihood criteria have been used. Thus by computing the distribution of rotated noisy samples, the optimum decoder is presented and its performance is analytically investigated. The privilege of this proposed algorithm is its inherent robustness against gain attack as well as its simplicity. Experimental results confirm the validity of the analytical derivations and also its high robustness against common attacks.

In this paper a very intelligent tool with low computational complexity is presented for Electroencephalogram (ECG) signal classification. The proposed classifier is based on Discrete Wavelet Transform (DWT) and Probabilistic Neural Network (PNN). The novelty of this approach is that signal statistics, morphological analysis and DWT of the histogram of signal (density estimation) altogether have been used to achieve a higher recognition rate. ECG signals and their density estimation are decomposed into sub-classes using DWT. A PNN is used to classify ECG signals using statistical discriminating features which are extracted from ECG and its sub-classes. Experimental results on five classes of ECG signals from MIT-BIH arrhythmia database show that the proposed method learns very fast, low computational complexity, and a very high performance compared to the previous methods.

In this paper two power elements for power controller in transmission line are presented: Variable Frequency Transformer (VFT) and Rotary Power Flow Controller (RPFC). In addition, here a new Optimal Power Flow (OPF) with these elements is presented. In this paper, it has been made use of the Impedance and Admittance nonsymmetrical matrix and the matrix of loss or coefficient B are calculated in a new method. It has also been indicated that the system is not optimized if optimal power flow is not considered in locating and power of flow controller in line. The proposed method was applied to a 26-bus and 6-generator system and the results were satisfactory

One of the most important stages in Character Recognition Systems is “Segmentation”, because any mistake will affect to all other tasks, especially to character recognition. This operation is more complex in Persian/Arabic writing than other Latin writing like English, and there has been an ongoing research on it. Other algorithms, that has been used as base as proposed algorithm, show 85% accuracy. In this paper, a new improved method has been presented by analyzing the visual features of the Persian/Arabic language. The proposed algorithm is able to segment existing fonts up to 98.5% accuracy or even 100% on some cases. The remaining error could be refined by applying a good character recognition technique and a precise vocabulary.

Minimizing mean tardiness by Job scheduling on parallel robots is very important in the scheduling domain. In this problem, there is a series of n-number independent jobs which are ready to be scheduled at the time of zero. Corresponding to each work, the processing time and duration date are determined. The aim of this approach is to find the order of jobs on the robots for minimizing the mean tardiness. This problem is in the class of NP-Hard combinational problems. Genetic algorithm is well known an effective tool for solving combinational optimization problems. In this study, an adaptive nonlinear genetic algorithm as well as two heuristic crossover and mutation operators are used. In the algorithm, there is a fitness function based on the mean tardiness. Therefore, the algorithm which can make the crossover and mutation probability adjusted adaptively and nonlinearly can avoid disadvantage such as premature convergence, low convergence speed and low stability. Experimental results demonstrate that the proposed genetic algorithm does not get stuck at a local optimum easily and yet it converges fast and is simple to implement.

In this paper, the direct torque control (DTC) technique is used for the speed control of induction motors, and then fuzzy logic is used for designing the speed controller, the improvement of torque response and the reduction of the speed error. The DTC method is utilized due to its quick torque response and robustness against sudden load variations. Also, by applying fuzzy logic unpredicted problems can be solved. The fuzzy logic also can improve the work of the speed control in induction motors. The results indicate that this approach improves the torque response significantly and reduces speed error.