Iranian Journal of Electrical and Electronic Engineering
Volume:13 Issue: 3, Sep 2017

The wavelet transform-domain least-mean square (WTDLMS) algorithm uses the self-orthogonalizing technique to improve the convergence performance of LMS. In WTDLMS algorithm, the trade-off between the steady-state error and the convergence rate is obtained by the fixed step-size. In this paper, the WTDLMS adaptive algorithm with variable step-size (VSS) is established. The step-size in each subfilter changes according to the largest decrease in mean square deviation. The simulation results show that the proposed VSS-WTDLMS has faster convergence rate and lower misadjustment than ordinary WTDLMS.

Differential Global Positioning System (DGPS) provides differential corrections for a GPS receiver in order to improve the navigation solution accuracy. DGPS position signals are accurate, but very slow updates. Improving DGPS corrections prediction accuracy has received considerable attention in past decades. In this research work, the Neural Network (NN) based on the Gaussian Radial Basis Function (RBF) has been developed. In many previous works all parameter of RBF NN are optimizing by evolutionary algorithm such as Particle Swarm Optimization (PSO), but in our approach shape parameter and centers of RBF NN are calculated in better way, in addition, search space for PSO algorithm will be reduced which cause more accurate and faster approach. The obtained results show that RMS has been reduced about 0.13 meter. Moreover, results are tabulated in the tables which verify the accuracy and faster convergence nature of our approach in both on-line and off-line training methods.

In this paper, the algorithms for adaptive rejection of a radar clutter are synthesized for the case of a priori unknown spectral-correlation characteristics at wobbulation of a repetition period of the radar signal. The synthesis of required algorithms for the non-recursive adaptive rejection filter (ARF) of a given order, which is used in modern radar systems, reduces to determination of the weighting coefficients vector, which realizes the best effectiveness index for radar signal extraction from the moving targets on the received clutter background. As the effectiveness criterion, we consider the averaged (over the Doppler signal phase shift) improvement coefficient for a signal-to-clutter ratio (SCR), which is usually used at describing the modern radars. On the base of extreme properties of the characteristic numbers (eigennumbers) of the matrices, the optimal vector is defined as the eigenvector of the correlation matrix of the clutter, corresponding to its minimal eigenvalue. After transition to the estimate value of the clutter correlation matrix according to the adaptive Bayesian approach, the general type of the vector of optimal ARF weighting coefficients is determined. The specific adaptive algorithms, depending upon the ARF order, are obtained, which in the particular cases can be reduced to the known algorithms confirming its authenticity. The comparative analysis of the synthesized and known algorithms is performed. It is shown that adaptation of offered processing algorithms in combination with its time adjustment leads to significant benefits in clutter rejection effectiveness compared to the known processing algorithms. Application of the algorithms obtained during ARF designing allows increase the effectiveness of radar signal extraction from the moving targets in much more range of its radial velocities on the clutter background in the case of unknown spectral-correlation properties.

An ultra-wide band band-pass filter using novel spiral stub-loaded triple-mode resonator (SSL-TMR) is presented. New spiral stub loaded resonator is analyzed with odd and even modes analysis for this class of BPF, achieving higher band wide and size reduction. In order to have a good response characterized, two (SSL-TMRs) and two quarter wavelength digital coupled lines are used. This new design filter produces triple modes, one odd mode and two even modes in the desired band and two transmission zeroes(TZs) out of band, providing sharp cut off, low insertion-loss and good return-loss characteristics. The measured results are in good agreement with the electromagnetic simulation.

Using composite right-left handed (CRLH) transmission line concept, a novel miniaturized dual notch band filter (DNBF) is proposed. The suggested DNBF consists of an interdigital transmission line (ITL), split ring resonators (SRRs) and complementary split ring resonators (CSRRs). Since the resonance frequency of the SRRs and CSRRs are quite independent of each other, the dual notch bands of the proposed filter can be separately controlled and shifted by changing the dimension of the SRRs and CSRRs. In this paper, the reject bands are designed for WLAN (2.4 GHz) and WiMAX (3.5 GHz) to reject these frequency bands from the ultra-wide band communication systems. The simulation results show that the transmission response has more than 32 dB rejections near each band. To validate the design concept, the proposed NBPF has been fabricated and tested. Experimental verification is provided and good agreement has been found between simulation and measurement. To the best of our knowledge, the proposed NBPF is more compact in comparison with other reported filters.

Image denoising as a pre-processing stage is a used to preserve details, edges and global contrast without blurring the corrupted image. Among state-of-the-art algorithms, block shrinkage denoising is an effective and compatible method to suppress additive white Gaussian noise (AWGN). Traditional NeighShrink algorithm can remove the Gaussian noise significantly, but loses the edge information instead. To overcome this drawback, this paper aims to develop an improvement shrinkage algorithm in the wavelet space based on the NeighSURE Shrink. We establish a novel function to shrink neighbor coefficients and minimize Stein’s Unbiased Risk Estimate (SURE). Some regularization parameters are employed to form a flexible threshold and can be adjusted via genetic algorithm (GA) as an optimization method with SURE fitness function. The proposed function is verified to be competitive or better than the other Shrinkage algorithms such as OracleShrink, BayesShrink, BiShrink, ProbShrink and SURE Bivariate Shrink in visual quality measurements. Overall, the corrected NeighShrink algorithm improves PSNR values of denoised images by 2 dB.

Specific and sensitive operation of circuit breakers makes an individual position for them in power networks. Circuit breakers are at the central gravity of variations and execution operations. Therefore, an optimum operation is the main reason to investigate about new gases to be used in MV and HV circuit breakers instead of SF6. The arc process has enormous complexity because of hydrodynamic and electromagnetic combination equations, and that is the exact reason why most of the previous simulations were processed in two-dimension analysis. But, in this paper a three-dimension simulation with sufficient results has been fully discussed. Different evaluations on the other gases have taken under study in order to find a suitable substitute instead of SF6 gas, which can also bring an optimum operation for the breakers and can be even friendly with the environment. The simulations have been carried out based on the finite element method (FEM) and magneto-hydrodynamic equations. A three-dimension model under the transient state has been chosen in the simulations to find a feasible substitute for SF6 gas. The main factors of the analysis are threefold as follows: arc temperature on the different regions, the cooling ability and arc resistance. CO2, CF3I and N2 are nominated to substitute the SF6 gas and their effects on cooling ability, nozzle evaporation, contacts erosion and arc resistance will be discussed.

This paper presents a new structure to provide the ability for power sharing of two Z-source inverters. According to the operation principles of Z-source inverters, only one input source supplies the circuit, which is a limitation particularly for the stand alone systems feeded by limited output power such as photovoltaics and feul cells. Furthermore; if one source fails to supply, the load cant be supplied. This paper covers those via interconnection of impedance network of two Z-source inverters. The operating principles of the proposed topology for the stand-alone and power sharing conditions are described and the relations are derived. The topology is simulated, which the results verify the theoretical analysis and well performance of the system.

In this paper, a new type of multi-variable compensation control method for the wind energy conversion systems (WECS) is presented. Based on wind energy conversion systems, combining artificial neural network (ANN) control and PID, a new type of PID NN intelligent controller for steady state torque of the wind generator is designed, by which the steady state torque output is regulated to track the optimal curve of wind power factor and the blade pitch angle is regulated to keep the stable power output. Also, the LPV model of the WECS, LPV compensator for the wind generator is designed to effectively compensate output of the wind generator torque and the blade pitch angle. Finally, simulation models of the control system based on a realistic model of a 8 kw wind turbines are built up based on the Dspace platform. The results show that the proposed method can reduce interferences caused by disturbed parameters of the WECS, mechanical shocks of the wind generator speed are reduced while capturing the largest wind energy fluctuation range of wind generator power output is reduced, and the working efficiency of the variable pitch servo system is improved.

Distribution systems can be operated in multiple configurations since they are possible combinations of radial and loop feeders. Each configuration leads to its own power losses and reliability level of supplying electric energy to customers. In order to obtain the optimal configuration of power networks, their reconfiguration is formulated as a complex optimization problem with different objective functions and network operating constraints. In this paper, a multi-objective framework is proposed for optimal network reconfiguration with objective functions of minimization of power losses, System Average Interruption Frequency Index (SAIFI), System Average Interruption Duration Index (SAIDI), Average Energy Not Supplied (AENS), and Average Service Unavailability Index (ASUI). The optimization problem is solved by the Imperialist Competitive Algorithm (ICA) as one of the most modern heuristic tools. Since objective functions have different scales, a fuzzy membership is utilized here to transform objective functions into a same scale and then to determine the satisfaction level of the afforded solution using the fuzzy fitness. The efficiency of the proposed method is confirmed by testing it on 32-bus and 69-bus distribution test systems. Simulation results demonstrate that the proposed method not only presents intensified exploration ability but also has a better converge rate compared with previous methods.