Journal of Modeling and Simulation in Electrical and Electronics Engineering
No. 0, 2015

In this paper a novel hybrid algorithm for harmonics estimation in power systems is proposed. The estimation of the harmonic components is a nonlinear problem due to the nonlinearity of phase of sinusoids in distorted waveforms. Most researchers implemented nonlinear methods to extract the harmonic parameters. However, nonlinear methods for amplitude estimation increase time of convergence. Hence, hybrid methods are used for the harmonics estimation. These methods use linear approaches for amplitude and nonlinear approaches for phase estimations. This paper focuses on introducing a fast and precise approach for harmonics estimation. This approach is based on a fast adaptive search method i.e., Adaptive Particle Swarm Optimization (APSO)for phase estimation and a linear estimator i.e., Least Squares (LS) for amplitude estimation. The speed of convergence and accuracy of estimation are the main contributions of the presented method. Obtained results by MATLAB codes indicate the accuracy and highperformance of the APSO-LS.

One of the most important parameters in evaluating a watermarking algorithm is its capacity. Generally, watermarking capacity is expressed by bits per pixel (bpp) unit measure. But this measure does not show what the side effects would be on image quality, watermark robustness and capacity. In this paper we propose a three dimensional measure named Capacity surface which shows the effects of capacity on visual quality and robustness. By this measure we can objectively find the amount of degradation and robustness for different capacities. Our experimental results are compatible with the previous related works in this field (about 20% tolerance) while provide more flexibility for capacity estimation in different conditions.

A fourth-degree Substrate Integrated Waveguide (SIW) crossed coupled band pass filter for WLAN band is designed by using a new negative coupling structure. It consists of two U shape microstrip lines on top and bottom planes with via holes at the center of them. This paper investigates the phase characteristics of negative and positive coupling structures and their effects. The design, fabrication and testing processes of the proposed filter are presented. The measured results seem to be consistent with the results obtained from simulator packages.

Due to the changes which may occur in their parameters, systems are usually demonstrated by some subsystems for different conditions. This paper employs Modified Petri Nets (MPN) to model theses subsystems and makes it simple to analyze them. In this method, first, the continuous transfer function is converted to a discrete transfer function and then, by MPN, system is modeled and analyzed. All subsystems can be modeled and used in state control or cascade control loops. Here, the focus is mainly on the conception as well as the definitions of the new unified representation model for continuous control systems. Simulation results show that the new method for modeling continuous systems works effectively.

In this study, a new servo control system is presented for the overhead crane based on discrete-time state feedback approach. It provides both robust tracking and load swing suppression. Inspired from independent joint and computed torque control in robot manipulator field, a new model is derived in which the crane actuators are considered as the main plant. The crane nonlinearities are then treated as disturbances acting on each actuator and being compensated via feedforward control. The load swing control is integrated to the servo controller through modifying the reference trolley acceleration. The stability of the tracking error and swing dynamics are proven based on error dynamic equation and passivity theory. Experimental results indicate the high performance and great potential for industrial application of the proposed control system.

Anomaly Detection (AD) has recently become an important application of target detection in hyperspectral images. The Reed-Xialoi (RX) is the most widely used AD algorithm that suffers from “small sample size” problem. The best solution for this problem is to use Dimensionality Reduction (DR) techniques as a pre-processing step for RX detector. Using this method not only improves the detection performance of algorithm, but also significantly reduces its runtime. This paper presents a novel DR technique that uses the Fast Fourier Transform (FFT) to perform the band reduction for RX detector. We compared the proposed method, named FFT-RX, with several well-known detectors such as RX, RX-UTD, KernelRX, PCA-RX and DWT-RX. These algorithms applied to two hyperspectral datasets acquired by both the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Hyperspectral Mapper (HyMap) sensors. The evaluation of algorithms was based on Receiver Operation Characteristic (ROC) curve, visual investigation, and runtime of algorithms as well. Experimental results show that the proposed method improves the detection performance and runtime of RX detector significantly and has the best runtime and detection performance among all methods.

Despite recent advances in video inpainting techniques, reconstructing large missing regions of a moving subject while its scale changes remains an elusive goal. In this paper, we have introduced a scale-change invariant method for large missing regions to tackle this problem. Using this framework, first the moving foreground is separated from the background and its scale is equalized. Then, a nonlinear dimension reduction is performed using manifold learning. We interpolate the missing values using motion analysis based on 3D body pose changing. The motion of the subject is considered as two different time series for which values are forecasted in the missing region. Since the subject motion may be non-periodic and forecasted series being different, a single series in the missing region is interpolated using blending of two forecasted series. Finally, the interpolated points are refined using weighted signal matching. In this method, a radial basis function (RBF) network has been used for mapping from spatial to manifold space. Experimental results, for a number of videos, show that the proposed approach is better than other methods and 3D body pose changing is smooth in the inpainted sequences.