Iranian Journal of Electrical and Electronic Engineering

An ultra-wideband (UWB) low-noise amplifier (LNA) with simultaneous noise and distortion cancellation is presented. This LNA utilizes a pMOS in weak inversion for second- and third-order distortion cancellation. By using two inductors, the effective bandwidth for noise/distortion cancellation and input matching are extended. This LNA has been designed in a 0.18-μm CMOS process. The noise figure is 3.8–4.45 dB, IIP3 is 15–20 dBm, IIP2 is 10–16 dBm, and S 11 is lower than −15 dB over 5.8–10.6 GHz. The voltage gain is 13.8 dB while drawing 8.3 mA from 1.8 V supply voltage.

Voltage instability is a major threat for security of power systems. Preserving voltage security margin at a certain limit is a vital requirement for today's power systems. Assessment of voltage security margin is a challenging task demanding sophisticated indices. In this paper, a new index based on the correlation characteristic of network voltage profile is proposed for the purpose of online voltage security assessment. Voltage profile comprising all bus voltages contains the effect of network structure, load-generation patterns and reactive power compensation on the system behaviour and voltage security margin. Therefore, the proposed index is capable to clearly reveal the effect of system characteristics and events on the voltage security margin. The most considerable feature of this index is its fast and easy calculation from synchronously measured voltage profile without any need to system modelling and simulation and without any dependency on network size. At any instant of system operation by merely measuring network voltage profile and no further simulation calculation this index could be evaluated with respect to a specific reference profile. The results show that the behaviour of this index with respect to the change in system security is independent of the selected reference profile. The simplicity and easy calculation make this index very suitable for online application. The proposed approach has been demonstrated on IEEE 39 bus test system with promising results showing its effectiveness and applicability.

Multilevel voltage source inverters have several advantages compare to traditional voltage source inverter. These inverters reduce cost, get better voltage waveform and decrease Total Harmonic Distortion (THD) by increasing the levels of output voltage. In this paper Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods are used to find the switching angles for achieving to the minimum THD for output voltage waveform of the Cascaded H-bridge Multi-Level Inverters (MLI). These methods are used for a 27-level inverter for different modulation indices. Result of two methods is identical and in comparison to other methods have the smallest THD. To verify results of two mentioned methods, a simulation using MATLAB/Simulink software is presented. © 2016, Iran University of Science and Technology. All rights reserved.

A 2D analytical method for magnetic vector potential calculation in inner rotor surface mounted and surface inset permanent magnet machines considering slotting effects, magnetization orientation and winding layout has been proposed in this paper. The analytical method is based on the resolution of Laplace and Poisson equations as well as Maxwell equation in quasi-Cartesian coordinate by using sub-domain method and hyperbolic functions. The developed method is applied on the performance computation of two prototypes surface mounted permanent magnet motors and two prototypes surface inset permanent magnet motors. A radial and a parallel magnetization orientation is considered for each type of motor. The results of these models are validated through FEM method. © 2017, Iran University of Science and Technology. All rights reserved.

In this paper, we propose a new path-based multicast algorithm that is called Row/Column-First algorithm. The proposed algorithm constructs a set of multicast paths to deliver a multicast message to all multicast destination nodes. The set of multicast paths are all of row-first or column-first subcategories to maximize the multicast performance. The selection of row-first or column-first approaches is done based on the location of multicast source node i.e., how the multicast source is far from right/left and top/bottom margins of the mesh network. In this way, the proposed algorithm improves two performance criteria i.e., traffic and communication latency as compared with the well-known Column-Path multicast algorithm. In order to evaluate the proposed algorithm, an analytical model is developed to estimate the mentioned performance criteria. The modeling and simulation results show improvement of 10 and 20 percent on traffic and communication latency respectively for Row/Column-First algorithm as compared to the Column-Path algorithm. © 2018, Iran University of Science and Technology. All rights reserved.

Resolvers are widely used in electric driven systems especially in high precision servomechanisms. Both encapsulated and pancake resolvers suffer from a major drawback: static eccentricity (SE). This drawback causes a significant increase in resolver output position error (RPE) which could not be corrected electronically. To reduce RPE, this paper proposes a novel structure with axial flux. Proposed topology, design guidelines, optimization procedure and several key features to improve the sensitivity of axial flux resolver (AFR) against SE are studied. Furthermore, to minimize RPE an optimized design is attained. The machines are investigated in detail by using d-q model and 3D time stepping finite-element analysis. The results of theses two methods are compared and both prototype machines (proposed and optimized) are built. In order to evaluate proposed topologies, an experimental test setup is devised. Finally, the experimental results of the prototype machines verified the analysis results.

A novel low-voltage two-stage operational amplifier employing resistive biasing is presented. This amplifier implements neutralization and correction common mode stability in second stage while employs capacitive dc level shifter and coupling between two stages. The structure reduces the power consumption and increases output voltage swing. The compensation is performed by simple miller method. For each stage an independent commonmode feedback circuits has been used. Simulation results show that power consumption is 2.1 mW at 1 V supply. The dc gain of the amplifier is about 70 dB while its output swing is as high as around 1.2 V.

Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss, etc. This paper presents a new methodology using Fuzzy and Artificial Bee Colony algorithm (ABC) for the placement of Distributed Generators (DG) in the radial distribution systems to reduce the real power losses and to improve the voltage profile. A two-stage methodology is used for the optimal DG placement. In the first stage, Fuzzy is used to find the optimal DG locations and in the second stage, ABC algorithm is used to find the size of the DGs corresponding to maximum loss reduction. The ABC algorithm is a new population based meta heuristic approach inspired by intelligent foraging behavior of honeybee swarm. The advantage of ABC algorithm is that it does not require external parameters such as cross over rate and mutation rate as in case of genetic algorithm and differential evolution and it is hard to determine these parameters in prior. The proposed method is tested on standard IEEE 33 bus test system and the results are presented and compared with different approaches available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.

In the present paper, the effects of aberration on the Bit-Error-Rate (BER) and reliability of Free-Space Optical (FSO) communication links are investigated. Based on aberrated divergent rectangular partially coherent flat-topped beam formula on the receiver plane and considering the atmosphere losses due to absorption, scattering and turbulence, numerical values for Power-In-Bucket (PIB), Signal to Noise Ratio (SNR) and BER are calculated. Using these values, the effects of source parameters on link reliability are described. The results are illustrated by graphs obtained by calculation and simulation.

This paper deals with the measurement of AC corona inception voltage, Vincp, at the tip of a rod electrode using a hemispherically-capped rod-plane electrode configuration for various rod radii with a short air gap. Effects of atmospheric pressure and temperature variation on Vincp are investigated experimentally. An empirical equation for the field form factors of the hemispherically capped rod-plane electrodes is proposed with its range of applicability. The obtained results are analyzed to derive a more accurate analytical equation for the calculation of the electric field at corona inception voltage, Eincp, and the average of electric field distribution, Emean

This paper presents a method to control both the dc boost and ac output voltages of Z-source inverter using neural network controllers. The capacitor voltage of the Z-source network has been controlled linearly in order to improve the transient response of the dc boost voltage of the Z-source inverter. The peak value of the line to line ac output voltage is used to control and keep the ac outputs to their desired values. A modified space vector pulse-width-modulation method is also applied to control the shoot-through duty ratio for boosting dc voltage. This modified method lets to minimize the dc voltage stress across the inverter switches. The neural network control technique is verified with simulation results and compared with the traditional PI controller responses.

The hybrid AC-DC microgrid (HMG) architecture has the merits of both DC and AC coupled structures. Microgrids are subject to intermittence when the renewable sources are used. In the HMG, since power fluctuations occur on both subgrids due to varying load and unpredictable power generation from renewable sources, proper voltage and frequency regulation is the critical issue. This article proposes a unique method for operating a microgrid (MG) comprising of PV array, wind energy system (WES), fuel cell (FC), and battery in HMG configuration. The control scheme of the interlinking converter (ILC) regulates frequency, voltage, and power flow amongst the subgrids. Power management in the HMG is investigated under different scenarios. Proper power management is accomplished within the individual subgrids and among the subgrids by the control techniques adopted in the HMG. The system voltage and frequency deviations are found to be minimized when the FC system acts as the backup source for DC subgrid, reducing the power flow through the ILC.

An inherent problem of single-phase rectifiers is the existence of a pulsating portion in the input power, which pulsates at twice the grid frequency. If this pulsating power is transferred to the DC-link, it causes a significant amount of second-order harmonic at the output voltage. Since in many applications, such a high level of DC oscillation is not acceptable, so the pulsating power must be effectively filtered. A convenient solution to eliminate the output voltage oscillations is to use a capacitor with a relatively high capacity at the rectifier output. Due to the fact that the high capacity capacitors for this application usually have a short lifetime and occupy a lot of space, this solution cannot be considered as a proper one. In this paper, a new active method with the minimum of current and voltage stress is proposed to effectively eliminate the pulsating power and significantly reduce the required capacitance of the output filter. The proposed method is able to reduce the volume of the converter and increase its reliability and power density. The validity and effectiveness of the proposed method are confirmed by extensive simulations in the MATLAB/Simulink. © 2018, Iran University of Science and Technology. All rights reserved.

Differential base station sometimes is not capable of sending correction information for minutes, due to radio interference or loss of signals. To overcome the degradation caused by the loss of Differential Global Positioning System (DGPS) Pseudo- Range Correction (PRC), predictions of PRC is possible. In this paper, the Support Vector Machine (SVM) and Genetic Algorithms (GAs) will be incorporated for predicting DGPS PRC information. This study uses GAs to select parameters of SVMs. Online training for real-time prediction of the PRC enhances the continuity of service on the differential correction signals and therefore improves the positioning accuracy in Real Time DGPS. Given a set of data received from low cost GPS module, the GASVM can predict the PRC precisely when the PRC signal is lost for a short period of time. This method which is introduced for the first time to predict of PRC is compared to other recently published methods. The time step of the prediction was six second. The experiments show that the total RMS prediction error of GASVM is less than 0.186m for one step and 0.76m for 10 step ahead cases.

In this paper, combined GPS and GLONASS positioning systems are discussed and some solutions have been proposed to improve the accuracy of navigation. Global Satellite Navigation System (GNSS) is able to provide position, velocity and time with respect to coordinated universal time. GNSS positioning is based on received satellite signals, so its performance is highly dependent on the quality of these received signals. The effect of noise and multi-path can often be large enough to produce significant errors in positioning. Satellite navigation is difficult in this situation. In such circumstances, GPS or GLONASS alone are often not able to ensure consistency and accuracy in positioning due to the absence (or low quality) of signals. The combination of these two systems is an appropriate solution to improve the situation. In positioning a receiver, one of the ways that is often used to reduce the error due to observation noise and calculation errors is Kalman Filter (KF) estimation. In this paper, some changes in the structure of the KF is applied to improve the accuracy of positioning. Process of updating KF's gain, is done in fuzzy form based on the parameters available in RINEX files, including the P code pseudo-range used as an input of the proposed fuzzy system. Simulation results show that applying a fuzzy KF based on P code pseudo-range on the available data sets, in terms of noise and blocking condition, reduces the positioning error respectively from 24 to 14 meters and 90 to 25 meters. © 2016, Iran University of Science and Technology. All rights reserved.

When a detector sensitive to the target plume IR seeker is used for tracking airborne targets, the seeker tends to follow the target hot point which is a point farther away from the target exhaust and its fuselage. In order to increase the missile effectiveness, it is necessary to modify the guidance law by adding a lead bias command. The resulting guidance is known as target adaptive guidance (TAG). First, the pure proportional navigation guidance (PPNG) in 3-dimensional state is explained in a new point of view. The main idea is based on the distinction between angular rate vector and rotation vector conceptions. The current innovation is based on selection of line of sight (LOS) coordinates. A comparison between two available choices for LOS coordinates system is proposed. An improvement is made by adding two additional terms. First term includes a cross range compensator which is used to provide and enhance path observability, and obtain convergent estimates of state variables. The second term is new concept lead bias term, which has been calculated by assuming an equivalent acceleration along the target longitudinal axis. Simulation results indicate that the lead bias term properly provides terminal conditions for accurate target interception.

One of the instruments for determination of position used in several applications is the Global Positioning System (GPS). With a cheap GPS receiver, we can easily find the approximate position of an object. Accuracy estimation depends on some parameters such as dilution of precision, atmospheric error, receiver noise, and multipath. In this study, position accuracy with GPS receiver is classified in three classes. Nine classification methods are utilized and compared. Finally, a new method is selected for classification. Results are verified with experimental data. Success rate for classification is approximately 84%. © 2016, Iran University of Science and Technology. All Rights Reserved.

In this paper, we study rate region of a Gaussian two-way diamond channel which operates in half- duplex mode. In the channel that we consider in this paper, Two Transceiver (TR) nodes exchange their messages with the cooperation of two relay nodes. We consider a special case of the Gaussian two-way diamond channels which is called Compute-and-Forward Multiple Access Channel (CF-MAC). In the CF-MAC, the TR nodes transmit their messages to the relay nodes which are followed by a simultaneous communication from the relay nodes to the TRs. Adopting rate splitting method in the terminal encoders and then using Compute-and-Forward (CF) relaying and decoding the sum of messages at the relay nodes, an achievable rate region for this channel is obtained. To this end, we use a superposition coding based on lattice codes. Using numerical results, we show that our proposed scheme outperforms the other similar methods and achieves a tighter gap to the outer bound. © 2015, Iran University of Science and Technology. All rights reserved.

In this paper, a novel design of all-solid photonic bandgap fiber with ultra-low confinement loss is proposed. The confinement loss is reduced remarkably by managing the number of rods rings, up-doping level, pitch value, and rods diameters. Moreover, the designed PCF shows ultra-flattened dispersion in L- and U-band. Furthermore, a new design, based on introducing of an extra ring of air holes on the outside of the all-solid bandgap structure, is then proposed and characterized. We demonstrate that it significantly reduces the fiber diameter to achieve negligible confinement loss. The validation of the proposed design is carried out by employing a two dimensional finite difference frequency domain with perfectly matched layers.

Recently, Inner permanent magnet (IPM) synchronous machines have been introduced as a possible traction motor in hybrid electric vehicle (HEV) and traction applications due to their unique merits. In order to achieve maximum torque per ampere (MTPA), optimization of the motor geometry parameters is necessary. This paper Presents a design method to achieve minimum volume, MTPA and minimum value of cogging torque for traction IPM synchronous machines and simulation in order to extract the output values of motor is done using 3D-Finite Element Model, that has high level of accuracy and gives us a better insight of motor performance. Then presents back EMF, power factor, cogging torque, Flux density, torque per ampere diagram, CPSR (constant power speed ratio), torque per speed diagram in this IPM synchronous machine. This study can help designers in design approach of such motors.

In this paper, a robust adaptive actuator failure compensation control scheme is proposed for a class of multi input multi output linear systems with unknown time-varying state delay and in the presence of unknown actuator failures and external disturbance. The adaptive controller structure is designed based on the SPR-Lyapunov approach to achieve the control objective under the specific assumptions and the SDU factorization method of the high frequency gain matrix is employed to drive the suitable form of the error equation. The two component controller structure with an integral term is used in order to compensate the effect of unknown state delay and external disturbance. Using a suitable Lyapunov-Krasovskii functional, it is shown that despite existing external disturbance and actuator failures, all closed loop signals are bounded and the plant Output asymptotically tracks the output of a stable reference model. Simulation results are provided to demonstrate the effectiveness of the proposed theoretical results. © 2017, Iran University of Science and Technology. All rights reserved.

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 algorithms for the non-recursive adaptive rejection filter (ARF) of a given order is reduced to determination of the vector of weighting coefficients, which realizes the best effectiveness index for radar signal extraction from the moving targets on the background of the received clutter. As the effectiveness criterion, we consider the averaged (over the Doppler signal phase shift) improvement coefficient for a signal-to-clutter ratio (SCR). On the base of extreme properties of the characteristic numbers (eigennumbers) of the matrices, the optimal vector (according to this criterion maximum) is defined as the eigenvector of the clutter correlation matrix corresponding to its minimal eigenvalue. The general type of the vector of optimal ARF weighting coefficients is de-termined and specific adaptive algorithms depending upon the ARF order are obtained, which in the specific cases can be reduced to the known algorithms confirming its authenticity. The comparative analysis of the synthesized and known algorithms is performed. Significant bene-fits are established in clutter rejection effectiveness by the offered processing algorithms compared to the known processing algorithms. © 2017, Iran University of Science and Technology. All rights reserved.

In this paper, we propose smart step closed-loop power control (SSPC) algorithm and base station assignment based on minimizing the transmitter power (BSAMTP) technique in a direct sequence-code division multiple access (DS-CDMA) receiver in the presence of frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with conjugate gradient (CG) adaptive beamforming algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference is canceled in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can be used for the MAI reduction in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly improve the network bit error rate (BER) in comparison with other algorithms. Also, we observe that significant savings in total transmit power (TTP) are possible with our proposed methods.

Performance of the linear models, widely used within the framework of adaptive line enhancement (ALE), deteriorates dramatically in the presence of non-Gaussian noises. On the other hand, adaptive implementation of nonlinear models, e.g. the Volterra filters, suffers from the severe problems of large number of parameters and slow convergence. Nonetheless, kernel methods are emerging solutions that can tackle these problems by nonlinearly mapping the original input space to the reproducing kernel Hilbert spaces. The aim of the current paper is to exploit kernel adaptive filters within the ALE structure for speech signal enhancement. Performance of these nonlinear algorithms is compared with that of their linear as well as nonlinear Volterra counterparts, in the presence of various types of noises. Simulation results show that the kernel LMS algorithm, as compared to its counterparts, leads to a higher improvement in the quality of the enhanced speech. This improvement is more significant for non-Gaussian noises. © 2017, Iran University of Science and Technology. All rights reserved.

Torque ripple minimization of switched reluctance motor drives is a major subject based on these drives' extensive use in the industry. In this paper, by using a well known cascaded torque control structure and taking the machine physical structure characteristics into account, the proposed energy-based (passivity-based) adaptive sliding algorithm derived from the viewpoint of energy dissipation, control stability and algorithm robustness. First, a nonlinear dynamic model is developed and decomposed into separate slow and fast passive subsystems that are interconnected by negative feedbacks. Then, an outer loop speed control is employed by adaptive sliding controller to determine the appropriate torque command. Finally, to reduce torque ripple in switched reluctance motor a high-performance passivity-based current controller is proposed. It can overcome the inherent nonlinear characteristics. The performance of the proposed controller algorithm has been demonstrated in simulation, and experimental using a 4KW, four-phase, 8/6 pole SRM DSP-based drive system.

In this paper, a new sensorless model reference adaptive method is used for direct control of active and reactive power of the doubly fed induction generator (DFIG). In order to estimate the rotor speed, a high frequency signal injection scheme is implemented. In this study, to improve the accuracy of speed estimation, two methods are suggested. First, the coefficients of proportional-integral (PI) blocks are optimized by using Krill Herd algorithm. In the second method, the fuzzy logic control method is applied in the estimator structure instead of PI controllers. The simulation results for the proposed methods illustrate that the estimated speed perfectly matches the actual speed of the DFIG. In addition, the desired slip value is achieved due to the accurate response. On the other hand, the active and reactive power responses have fast dynamics and relatively low oscillations. Moreover, the fuzzy controller shows more robustness against the variations of machine parameters. © 2018, Iran University of Science and Technology. All rights reserved.

When the process is highly uncertain, even linear minimum phase systems must sacrifice desirable feedback control benefits to avoid an excessive 'cost of feedback', while preserving the robust stability. In this paper, the problem of supervisory based switching Quantitative Feedback Theory (QFT) control is proposed for the control of highly uncertain plants. According to this strategy, the uncertainty region is suitably divided into smaller regions. It is assumed that a QFT controller-prefilter exits for robust stability and performance of the individual uncertain sets. The proposed control architecture is made up by these local controllers, which commute among themselves in accordance with the decision of a high level decision maker called the supervisor. The supervisor makes the decision by comparing the candidate local model behavior with the one of the plant and selects the controller corresponding to the best fitted model. A hysteresis switching logic is used to slow down switching for stability reasons. Besides, each controller is designed to be stable in the whole uncertainty domain, and as accurate in command tracking as desired in its uncertainty subset to preserve the robust stability from any failure in the switching.

This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison with NSAF, the VSS-NSAF algorithm has faster convergence speed and lower MSD. To reduce the computational complexity of VSSNSAF, the VSS selective partial update NSAF (VSS-SPU-NSAF) is proposed where the filter coefficients are partially updated in each subband at every iteration. We demonstrated the good performance of the proposed algorithms in convergence speed and steady-state MSD for a system identification set-up.

The Global Positioning System (GPS) signals are very weak signal over wireless channels, so they are vulnerable to in-band interferences. Therefore, even a low-power interference can easily spoof GPS receivers. Among the variety of GPS signal interference, spoofing is considered as the most dangerous intentional interference. The spoofing effects can mitigate with an appropriate strategy in the receiver. In this paper, we use methods of adaptive filter based on Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) algorithms in order to defense against spoofing. The new approaches based on LMS and NLMS are applied in the acquisition stage of the receiver. The new approaches are operated to mitigate effect of spoofing from the received signal in GPS valid receiver. LMS-based algorithm is a class of adaptive filter that modify the filter coefficients to minimize the error signal. NLMS algorithm is a modified form of the normal LMS algorithm that solves the LMS problem by normalizing with the power of the input signal. The proposed methods have been implemented on real dataset. The results explain that the suggested algorithms significantly decrease spoofing. Also, they improve Position Dilution of Precision (PDOP) parameter. Based on the results, NLMS algorithm has better performance than LMS algorithm. © 2015, Iran University of Science and Technology. All Rights Reserved.

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. © 2017, Iran University of Science and Technology. All rights reserved.

Due to widespread use of Global Positioning System (GPS) in different applications, the issue of GPS signal interference cancelation is becoming an increasing concern. One of the most important intentional interferences is spoofing signals. An effective interference (delay spoof) reduction method based on adaptive filtering is developed in this paper. The principle of method is using adaptive filters to eliminate interference, obtain an estimate of interfering signal and subtract that from the corrupted signal. So, what remains in the output is the desired signal. Here, for updating the filter coefficients adaptive algorithms in both time (statistical and deterministic) and transform domain will be studied. The proposed adaptive filter is applied to a batch of spoofing GPS data in pseudo-range level. The results indicate that all investigated algorithms are able to reduce positioning steady-state miss-adjustment up to 70 percent. In this context, the variable step-size least mean square algorithm performs better than others do. © 2018, Iran University of Science and Technology. All rights reserved.

In this paper, a new guidance law is designed to improve the performance of a homing missiles guidance system in terminal phase. For this purpose first of all, the two dimensions equations of motion are formulated, then the approximation dynamic of missile control loop is added to these equations which are nonlinear whit unmatched uncertainty. Then, a new adaptive back-stepping method is developed in order to control this system. An adaptive term is used in the control law that is converged to the uncertainty. This convergence is proved based on Lyapunov stability theorem. Therefore using this adaptive term in the control law can be eliminated the uncertainty. Based on this algorithm, a new guidance law is designed. Then its performance is compared with common guidance laws in a guidance loop simulation in the presence of control loop dynamics. © 2018, Iran University of Science and Technology. All rights reserved.

Two-dimensional (2D) adaptive filtering is a technique that can be applied to many image and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to 2D structure and the novel 2D adaptive filters are established. Based on this extension, the 2D variable step-size normalized least mean squares (2D-VSS- NLMS), the 2D-VSS affine projection algorithms (2D-VSS-APA), the 2D set-membership NLMS (2D-SM-NLMS), the 2D-SM-APA, the 2D selective partial update NLMS (2D- SPU-NLMS), and the 2D-SPU-APA are presented. In 2D-VSS adaptive filters, the step- size changes during the adaptation which leads to improve the performance of the algorithms. In 2D-SM adaptive filter algorithms, the filter coefficients are not updated at each iteration. Therefore, the computational complexity is reduced. In 2D-SPU adaptive algorithms, the filter coefficients are partially updated which reduce the computational complexity. We demonstrate the good performance of the proposed algorithms thorough several simulation results in 2D adaptive noise cancellation (2D-ANC) for image denoising. The results are compared with the classical 2D adaptive filters such as 2D-LMS, 2D-NLMS, and 2D-APA.

This paper presents a high-speed, low-power and low area encoder for implementation of flash ADCs. Key technique for design of this encoder is performed by convert the conventional 1-of-N thermometer code to 2-of-M codes (M = ¾ N). The proposed encoder is composed from two-stage; in the first stage, thermometer code are converted to 2-of-M codes by used 2-input AND and 4-input compound AND-OR gates. In the second stage by two ROM encoders, 2-of-M codes determine n-1 MSB bits and one LSB bit. The advantages of the proposed encoder rather than other similar works are high speed, low power consumption, low active area, and low latency with same bubble error removing capability. To demonstrate the mention specifications, 5-bit flash ADCs with conventional and proposed encoders in their encoder blocks, are simulated at 2-GS/s and 3.5-GS/s sampling rates in 0.18-μm CMOS process. Simulation results show that the ENOB of flash ADCs with conventional and proposed encoders are equal. In this case, the proposed encoder outputs are determined almost 30-ps faster rather than the conventional encoder at 2-GS/s. Also, the power consumptions of the conventional and proposed encoders were 17.94-mW and 11.74-mW at 3.5-GS/s sampling rate from a 1.8-V supply, respectively. Corresponding, latencies of the conventional and proposed encoders were 3 and 2 clock cycles. In this case, number of TSPC D-FFs and logic gates of the proposed encoder is decreased almost 39% compared to the conventional encoder. © 2018, Iran University of Science and Technology. All rights reserved.

In this paper a new mathematical model is developed for the dynamics between tumor cells, normal cells, immune cells, chemotherapy drug concentration and drug toxicity. Then, the theorem of Lyapunov stability is applied to design treatment strategies for drug protocols that ensure a desired rate of tumor cell kill and push the system to the area with smaller tumor cells. Using of this theorem a condition for drug administration to patients so that solution of the system of equations always tends to tumor free equilibrium point is proposed.

The switched reluctance motor is a singly excited, doubly salient machine which can be used in generation mode by selecting the proper firing angles of the phases. Due to its robustness, it has the potential and the ability to become one the generators to be used in harsh environment. This paper presents an energy conversion by a Switched Reluctance Generator (SRG) when bifilar converter circuit and discrete position sensors are employed. As the generator’s speed increases by a prime mover the shape of current waveform changes in such a way that limits the production of generating voltage. At high speeds, it is possible for the phase current never reaches the desired value to produce enough back-emf for sufficient voltage generation, therefore, the output power falls off. In order to remedy this problem, the phase turn on angle is advanced in a way that the phase commutation begins sooner. Since one of the advantages of this type of generator is its variable speed then, the amount of advancing for the turn on angle should be accomplished automatically to obtain the desired output voltage according to the speed of the generator, meaning, as the generator speed increases so should the turn on angle and vice versa. In this respect, this paper introduces an electronic circuit in conjunction with the position sensors and the drive converter to achieve this task for a desired output voltage when a SRG feeding a resistive load. To evaluate the generator performance, two types of analysis, namely numerical technique and experimental studies have been utilized on a 6 by 4, 30 V, SRG. In the numerical analysis, due to highly non-linear nature of the motor, a three dimensional finite element analysis is employed, whereas in the experimental study, a proto-type generator and its circuitries have been built and tested using bifilar converter. A linear analysis of the current waveform for the generator under different advancements of the turn on angle has been performed numerically and experimentally and the results are presented.

Differential Power Analysis (DPA) implies measuring the supply current of a cipher-circuit in an attempt to uncover part of a cipher key. Cryptographic security gets compromised if the current waveforms obtained correlate with those from a hypothetical power model of the circuit. During last years, there has been a large amount of work done dealing with the algorithmic and architectural aspects of cryptographic schemes implemented on FPGAs.* * However, there are only a few articles that assess their vulnerability to such attacks which, in practice, pose far a greater danger than algorithmic attacks. This paper first demonstrates the vulnerability of the Advanced Encryption Standard Algorithm (AES) implemented on a FPGA and then presents a novel approach for implementation of the AES algorithm which provides a significantly improved strength against differential power analysis with a minimal additional hardware overhead. The efficiency of the proposed technique was verified by practical results obtained from real implementation on a Xilinx Spartan-II FPGA.

Load side management is the basic and significant principle to keeping the balance between generation side and consumption side of electrical power energy. Load side management on typical medium voltage feeder is the power energy consumption control of connected loads with variation of essential parameters that loads do reaction to their variation. Knowing amount of load’s reaction to each parameters variation in typical medium voltage feeder during the day, leads to gain Load Manageability Factor (LMF) for that specific feeder that helps power utilities to manage their connected loads. Calculating this LMF needs to find out each types of load with unique inherent features behavior to each parameters variation. This paper results and future work results will help us to catch mentioned LMF. In this paper analysis of residential load behavior due to temperature variation with training artificial neural network will be done. Load behavior due to other essential parameters variations like energy pricing variation, major event happening, and power utility announcing to the customers, and etc will study in future works. Collecting all related works results in a unit mathematical equation or an artificial neural network will gain LMF. © 2016, Iran University of Science and Technology. All rights reserved.

Bayesian Networks (BN) provides a robust probabilistic method of reasoning under uncertainty. They have been successfully applied in a variety of real-world tasks but they have received little attention in the area of load-frequency control (LFC). In practice, LFC systems use proportional-integral controllers. However since these controllers are designed using a linear model, the nonlinearities of the system are not accounted for and they are incapable to gain good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem due to the distributed nature of a multi-area power system, is presented by using a BN multi-agent system. This method admits considerable flexibility in defining the control objective. Also BN provides a flexible means of representing and reasoning with probabilistic information. Efficient probabilistic inference algorithms in BN permit answering various probabilistic queries about the system. Moreover using multi-agent structure in the proposed model, realized parallel computation and leading to a high degree of scalability. To demonstrate the capability of the proposed control structure, we construct a BN on the basis of optimized data using genetic algorithm (GA) for LFC of a three-area power system with two scenarios.

This paper presents an online two-stage Q-learning based multi-agent (MA) controller for load frequency control (LFC) in an interconnected multi-area multi-source power system integrated with distributed energy resources (DERs). The proposed control strategy consists of two stages. The first stage is employed a PID controller which its parameters are designed using sine cosine optimization (SCO) algorithm and are fixed. The second one is a reinforcement learning (RL) based supplementary controller that has a flexible structure and improves the output of the first stage adaptively based on the system dynamical behavior. Due to the use of RL paradigm integrated with PID controller in this strategy, it is called RL-PID controller. The primary motivation for the integration of RL technique with PID controller is to make the existing local controllers in the industry compatible to reduce the control efforts and system costs. This novel control strategy combines the advantages of the PID controller with adaptive behavior of MA to achieve the desired level of robust performance under different kind of uncertainties caused by stochastically power generation of DERs, plant operational condition changes, and physical nonlinearities of the system. The suggested decentralized controller is composed of the autonomous intelligent agents, who learn the optimal control policy from interaction with the system. These agents update their knowledge about the system dynamics continuously to achieve a good frequency oscillation damping under various severe disturbances without any knowledge of them. It leads to an adaptive control structure to solve LFC problem in the multi-source power system with stochastic DERs. The results of RL-PID controller in comparison to the traditional PID and fuzzy-PID controllers is verified in a multi-area power system integrated with DERs through some performance indices. © 2017, Iran University of Science and Technology. All rights reserved.

In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA) energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP) agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offered real time prices, an hourly acceptance function is proposed in order to represent the hourly changes in the customer's effective demand according to the prices. Here, Q-learning (QL) approach is applied in day-ahead real time pricing for the customers enabling the REP agent to discover which price yields the most benefit through a trial-and-error search. Numerical studies are presented based on New England day-ahead market data which include comparing the results of RTP based on QL approach with that of genetic-based pricing.

In a typical competitive electricity market, a large number of short-term and long-term contracts are set on the basis of energy price by an Independent System Operator (ISO). Under such circumstances, accurate electricity price forecasting can lead to the more reasonable bidding strategies adopted by the electricity market participants. Using this prediction, the participants raise their profit and manage the relevant market more efficiently. This conspicuous reason has motivated the researchers to develop the most accurate, though sophisticated, forecasting models to predict the short-term electricity price as precisely as possible. In this article, a new method is suggested to forecast the next day's electricity price of Iranian Electricity Market. The authors have used this hybrid model successfully in their previous papers to predict the electric load data of Ontario Electricity Market and of the operating reserve data of Khorasan Electricity Network.

In this article, we present a new design of a coplanar waveguide fed (CPW-fed) ultra-wideband (UWB) antenna with dual band-notched characteristics. Two notched frequency bands are achieved by using two inverted U-shaped stepped impedance resonators. The proposed antenna can operate from 2.82 to 11 GHz (118%), defined by VSWR< 2, except two notched bands around 3.5 GHz (WiMAX) and 5.5 GHz (WLAN). The size of the antenna is 20×20×1.6 mm3. The experimental and simulated results of the prototyped antenna, including voltage standing wave ratio (VSWR), radiation pattern, and gain characteristics are presented and discussed. In addition, Analytical Hierarchy Process (AHP) method used for comparison the proposed antenna with previous designed structures. © 2017, Iran University of Science and Technology. All rights reserved.

The air-gap of electrical machines may become non-uniform due to low accuracy of the manufacturing machinery, in assembling processes, or by aging. Detection and monitoring of this phenomenon is very important and of interest. There are several methods to model non-uniform air-gaps and to detect them by monitoring systems. One of the most widely used methods is by the analysis of the line currents. In this paper a new, simple and comprehensive method is presented to model and detect non-uniform air-gaps in synchronous generators with skewed rotors. The influence of non-uniform air-gaps on the harmonics of the induced voltage of the stator is investigated by the proposed method. Simulations are performed for three cases: uniform air-gap, static rotor eccentricity, and stator ovality in a two phase generator. The experimental results are also presented. The good correspondence between the simulation and the experimental results clearly validates the theoretical findings put forward in this paper.

In this paper we introduce two innovative image and video watermarking algorithms. The paper’s main emphasis is on the use of chaotic maps to boost the algorithms’ security and resistance against attacks. By encrypting the watermark information in a one dimensional chaotic map, we make the extraction of watermark for potential attackers very hard. In another approach, we select embedding positions by a two dimensional chaotic map which enables us to satisfactorily distribute watermark information throughout the host signal. This prevents concentration of watermark data in a corner of the host signal which effectively saves it from being a target for attacks that include cropping of the signal. The simulation results demonstrate that the proposed schemes are quite resistant to many kinds of attacks which commonly threaten watermarking algorithms.

Impressive development of computer networks has been required precise evaluation of efficiency of these networks for users and especially internet service providers. Considering the extent of these networks, there are numerous factors affecting their performance and thoroughly investigation of these networks needs evaluation of the effective parameters by using suitable tools. There are several tools to measure network's performance which evaluate and analyze the parameters affecting the performance of the network. D-ITG traffic generator and measuring tool is one of the efficient tools in this field with significant advantages over other tools. One of D-ITG drawbacks is the need to determine input parameters by user in which the procedure of determining the input variables would have an important role on the results. So, introducing an automatic method to determine the input parameters considering the characteristics of the network to be tested would be a great improvement in the application of this tool. In this paper, an efficient method has been proposed to determine optimal input variables applying evolutionary algorithms. Then, automatic D-ITG tool operation would be studied. The results indicate that these algorithms effectively determine the optimal input variables which significantly improve the D-ITG application as the time cost of determining optimal DITG variables in automatic GA, ICA and ACO based methods has been improved up to 67.3%, 69.7% and 82.2%, respectively. © 2015, Iran University of Science and Technology, All Rights Reserved.

In this paper, optimal placement of Phasor Measurement Unit (PMU) using Global Positioning System (GPS) is discussed. Ant Colony Optimization (ACO), Simulated Annealing (SA), Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are used for this problem. Pheromone evaporation coefficient and the probability of moving from state x to state y by ants are introduced into the ACO. The modified algorithm overcomes the ACO in obtaining global optimal solution and convergence speed, when applied to optimize the PMU placement problem. We also compare this simulation with SA, PSO and GA to examine the capability of ACO in the search of optimal solution. The fitness function includes observability, redundancy and the number of PMU. Logarithmic Least Square Method (LLSM) is used to calculate the weights of fitness function. The suggested optimization method is applied in 30-bus IEEE system and the simulation results show that modified ACO results are better than PSO and SA, but it has nearly the same results as GA.

This paper proposes an algorithm for transmission cost allocation (TCA) in a large power system based on nodal pricing approach with multiarea scheme. The nodal pricing approach is introduced to allocate the transmission costs using the nodal pricing control in a single area network. As the number of equations is dependent on the number of buses and generators, this method will be very time consuming for large power systems. To solve this problem, the present paper proposes a new algorithm based on multiarea approach for regulating the nodal prices, so that the simulation time is greatly reduced and therefore the nodal pricing approach can be applicable for large power systems. In addition, in the proposed method, the transmission costs are allocated to the users more equitable than the single area method. Since the higher transmission costs of an area due to its higher reliability are paid only by users of that area in contrast with the single area method, in which these costs are allocated to all users regardless of their locations. The proposed method was implemented on the IEEE 118 bus test system having three areas. The obtained results show that with the application of multiarea approach, the simulation time is greatly reduced and the transmission costs are also allocated to users with less variation in new nodal prices with respect to the single area approach.

Node cooperation can protect wireless networks from eavesdropping by using the physical characteristics of wireless channels rather than cryptographic methods. Allocating the proper amount of power to cooperative nodes is a challenging task. In this paper, we use three cooperative nodes, one as relay to increase throughput at the destination and two friendly jammers to degrade eavesdropper’s link. For this scenario, the secrecy rate function is a non-linear non-convex problem. So, in this case, exact optimization methods can only achieve suboptimal solution. In this paper, we applied different meta-heuristic optimization techniques, like Genetic Algorithm (GA), Partial Swarm Optimization (PSO), Bee Algorithm (BA), Tabu Search (TS), Simulated Annealing (SA) and Teaching-Learning-Based Optimization (TLBO). They are compared with each other to obtain solution for power allocation in a wiretap wireless network. Although all these techniques find suboptimal solutions, but they appear superlative to exact optimization methods. Finally, we define a Figure of Merit (FOM) as a rule of thumb to determine the best metaheuristic algorithm. This FOM considers quality of solution, number of required iterations to converge, and CPU time. © 2017, Iran University of Science and Technology. All rights reserved.

This paper presents a method to allocate the transmission network costs to users based on nodal pricing approach by regulating the nodal prices from the marginal point to the new point. Transmission nodal pricing based on marginal prices is not able to produce enough revenue to recover the total transmission network costs. However, according to the previous studies in this context, this method recovers only a portion of transmission costs. To solve this problem, in this paper a method is presented in which by considering the direction and amount of injected power in each node the marginal price is regulated to the new price, in such a way as the nodal pricing can recover the total transmission network costs. Also the proposed method is able to control the cost splitting between loads and generators in accordance with the pre-specified ratio. The proposed method is implemented on both IEEE 24-bus and 118-bus test systems and the obtained results are reported.