Scientia Iranica
Volume:21 Issue: 6, 2014

Performability is an important parameter in safety-critical real-time systems. This parameter is defined as the joint consideration of two other important parameters, i.e., reliability and performance. This paper proposes a schedulability condition, which guarantees a desired level of performability in various working conditions, for real-time systems. The basic idea underlining this condition is to select a subset of schedulable tasks and manage their slack times to satisfy a desired performability level. The proposed condition is evaluated on a hard real-time system that employs the Rate-Monotonic (RM) scheduling algorithm and uses the re-execution mechanism to improve the reliability. Evaluation results reveal that by employing the condition, the level of performability of the system is always greater than the desired performability. In addition, it yields on average 1% improvement in the system performability in comparison with traditional schedulability conditions, while the actual failure rate is greater than the expected rate. This amount of performability improvement is significant for safety-critical real-time systems.

In this paper, we study the problem of online conflict-free coloring of intervals on a line, where each newly inserted interval must be assigned a color upon insertion such that the coloring remains conflict-free, i.e. for each point p in the union of the current intervals, there must be an interval I with a unique color among all intervals covering p. We fi rst present a simple algorithm which uses O(pn) colors where n is the number of current intervals. Next, we propose an CF-coloring of intervals which uses O(log3 n) colors.

Spanners generated by the greedy algorithm{or greedy spanners{not only have good theoretical properties, like a linear number of edges, low degree and low weight, but previous experimental results also show that they are superior to spanners generated by other algorithms in practice. Because of the good properties of greedy spanners, they found several applications like in protein visualization. The major issue in computing greedy spanners is the high time and space complexity of algorithms that compute it. To construct the greedy spanner on a set of n points, the original greedy algorithm takes O(n3 log n) time. In 2005, an improvement was proposed by Farshi and Gudmundsson [Lecture Notes in Computer Science, Vol. 3669, pages 556{567] that works much faster in practice, but later it was shown that it has same theoretical time complexity. In 2008, Bose et al. [Lecture Notes in Computer Science, Vol. 5124, pages 390{401] discovered a near-quadratic time algorithm for constructing greedy spanners. In this paper, we compare time complexity of these three algorithms for computing the greedy spanner in practice.

In flexible manipulators, the residual vibration and unwanted transient deflection are critical issues that are highly correlated with the velocity operation of the system; as the velocity increases the control of such systems become more delicate and difficult. The wiper blades of automobiles are among those types of flexible system that are required to be operated at quite high velocity to be ecient under high load conditions. This causes some annoying noise and deteriorated vision for travellers. The modelling and control of the vibration and low frequency noise of an automobile wiper blade is the focus of this study. The flexible vibration and noise model of a wiper system is estimated using an arti cial intelligence system identi cation approach. A controller approach is also developed to suppress the low frequency noise of a wiper end-point, while maintaining the desired position accuracy of the hub angle, simultaneously.

Active filters areeffective solutionsto eliminateharmonic pollutionandimproving the reactive powerin the presenceofnonlinear loadsandunbalanced sources. To reduce the disturbances caused by this type of load, we propose in this paper a new control strategy of shunt active filter. Our method aims to improve the electrical quantity behavior in steady and dynamic states while reducing the installing cost of the filter through by eliminating the AC line voltage sensors. It’s established by the direct power control (DPC) based on virtual flux (VF) estimation of the electrical network using switching function table. Facing to disturbances affecting the electrical network, we have integrated a phase locked loop (PLL). Indeed, we have implemented and tested our new control strategy in the Matlab / Simulink environment. The results obtained show the effectiveness of the active filter control algorithm to eliminate harmonic currentsand the improvement of the reactive power injected from nonlinear loads which allowed us to confirm the robustness of the proposed strategy.

One of the important capabilities of Plug in Hybrid Electric Vehicle (PHEVs) is injecting/absorbing harmonic current to/from grid. In this paper, a multiobjective framework is proposed to improve power quality of grid by PHEVs. In this study, each PHEV is modeled as an injected harmonic current source including different harmonic orders. The objective functions are: Total Harmonic Distortion (THD) of network nodes and Total PHEV Current (TPC) index both to be minimized. The multiobjective optimization problem is solved by ε-constraint method. The best compromise solution among various non-dominated (Pareto optimal) solutions is chosen based on a fuzzy approach. A typical 14-node microgrid test system is considered in the case study to examine the effectiveness of the proposed method.

Recently, it has been shown that applying MIMO technology, i.e. using multiple antennas at the transmit side and multiple antennas at the receive side, improves the performance of object detection and localization. In such scenarios, the spatial diversity specifically helps overcome the fading of cross section of the object leading to reduced probability of missed detection. Such phenomenon is in fact the dual of probability of bit error reduction in communication systems due to diversity gain. Despite the importance of such performance enhancement, this subject is not sufficiently investigated in the PCL (Passive Coherent Location) schemes, where the transmitters(or illuminators of opportunity) used for localization are already present in the environment. Especially in the case where the transmitters are working in a SFN (single frequency network), such as the DVB-T (Digital Video Broadcasting - Terrestrial) signal, and all are transmitting the same signal, the situation becomes of higher importance. Obviously, the effect of SFN environment, invalidates the assumption of sending orthogonal waveforms traditionally used in localization schemes. In this paper, we design the Neyman-Pearson detector for a PCL scheme and show that we can achieve the desired diversity gain for such design as well.

In this paper, a novel compensator based on Magnetically Controlled Reactor with Fixed Capacitor banks (FC-MCR) is introduced and then power system stability in presence of this compensator has been studied using intelligent control method. The problem of robust FC-MCR based damping controller design is formulated as a multi-objective optimization problem. The multi-objective problem is concoctedto optimize a composite set of two eigenvalue-based objective functions comprising the desired damping factor, and the desired damping ratio of the lightly damped and undamped electromechanical modes.The controller is automatically tuned with optimization of an eigenvalue based multi-objective function by ICAto simultaneously shift the lightly damped and undamped electromechanical modes to a prescribed zone in the s-plane so that the relative stability is guaranteed and the time domain specifications concurrently secured. The effectiveness of the proposed controller is demonstrated through eigenvalue analysis, nonlinear time simulation studies and some performance indices to damp low frequency oscillations under different operating conditions. The results show that the tuned ICA based FC-MCR controller which is designed by using the proposed multi-objective function has an outstanding capability in damping power system low frequency oscillations and significantly improves the power systems dynamic stability.

In this paper, we propose a two dimensional (2-D) optimal linear detector (OLD) for radar target detection in compound Gaussian clutter and obtain an explicit relation of its coefficients for slowly fluctuating targets. We assume that the samples of signal and clutter are correlated in both range and azimuth directions, and the target detection in each radar cell is implemented by a 2-D samples collection of the received signal. In most conventional detectors, in each pulsation interval, the samples of echo of each radar cell are passed through a matched filter along the range, and a pre-detection is performed; then the binary results are integrated for successive echoes of that cell (along the azimuth). In fact, by applying the binary integration, we ignore the considerable correlation among 2-D data in the azimuth direction. In the proposed 2-D OLD detector, the correlation of signal and clutter in both range and azimuth directions is considered, aiming to improve the detection performance. Our simulations confirm that, this detector outperforms the conventional one dimensional OLD, as well as AND, OR, and”κ out of n” binary integrators.

This paper presents a model of a feed forward arti cial neural network to predict the material removal rate of an electrical discharge machine process. A new modi ed architecture and training algorithm is proposed by segmenting the roughing and fi nishing machining parameters of the process. The segmentation is performed in order to obtain a lower di erence between the actual and predicted material removal rates. Through comparative analysis and results obtained between the two architectures, it is found that the new modi ed feed forward arti cial neural network produces lower error between the experimental and predicted material removal rates, thus, improving the accuracy of the prediction model.

DC microgrids and distribution systems will have an important role in the future electrical power system, i.e., smart grids. One of the most important issues of dc microgrids and distribution systems is the correct and fair determination of the energy prices of the consumers. In this paper, a novel, practical, accurate, fair nodal price, namely the real nodal price, is proposed to determine the energy payments of the consumers in dc microgrids and distribution systems. Applying the real nodal price, each consumer will exactly pay for its real energy costs, i.e., its accurate consumed energy and originated energy loss. The real nodal price is applicable to different dc microgrids and distribution systems, even those with mesh configuration and numerous distributed generators. The real nodal price leads to zero merchandising surplus. Besides, through the presented novel method in this paper, the real nodal price is computed by a few simple and fast calculations. Also, no slack bus is necessary to be assigned to compute the real nodal price. In this paper, the real nodal prices of a dc microgrid are derived through the presented method. The analyses and simulation results confirms the mentioned remarkable features of the real nodal price.

A new approach for the design of two-stage Miller-compensated CMOS op amps is presented. The paper studies the basic relations between power consumption, unity-gain bandwidth, biasing region, technology parameters, and the external capacitive load. As a result, simple and ecient design guides are provided to achieve the minimum possible power consumption for the given speci cations and for short-channel devices. It is shown that the conventional design proce- dures do not always result in minimum power op amps. The presented results are also veri ed by Spectre simulations.

In this study, a collocation method based on the Bernoulli polynomials is presented to find approximate solutions of a system of high-order linear Volterra integral equations (VIEs) with variable coefficients. In fact, the approximate solution of the problem in the truncated Bernoulli series form is obtained by this method. In addition, the method is presented with error and stability analysis. To show the accuracy and the efficiency of the method, numerical examples are implemented and the comparisons are given by the other methods.

Ubiquitous power-law as a fingerprint of Self-Organized Criticality (SOC) is used for describing catastrophic events in different fields. In this paper, by investigating the prerequisites of SOC, we show that SOC-like dynamics drive correlation among disturbances in Iran bulk power system. Existence of power-law region in the probability distribution is discussed for empirical data using Maximum likelihood estimat­ion. To verify the results, long time correlation is evaluated in terms of Hurst exponents by means of statistical analysis of time series including Rescaled Range (R/S) and Scaled Windowed Variance (SWV) analysis. Also, Sensitivity analysisshowed that for correct inference in existence of SOC in power systems, all disturbances should berecorded to be used in statistical analyses. Greater thresholds for recording disturbances lead to underestimate the Hurst exponent.

Photovoltaic energy has nowadays an increased importance in electrical power applications. However, the output power provided via the photovoltaic conversion process depends on solar irradiation and temperature. Tracking the maximum power point (MPP) ofphotovoltaic (PV) systems is the most important part ofthe PV systems. Inthis paper, modeling and parametersextraction method are proposed to describe the optimal current, voltage and power of the photovoltaic cells. The aim is to find a formula that considers these factors and to study the interactions between these various factors. Design of experiments is a powerful tool to understand systemsand processes. Experiments are often run so that the effect of one factor is unknowingly confused with the effect of another factor. A brief comparison between the classic modeling is presented. In order to model the optimal current, optimal tension and optimal power, a methodology of experimental design is presented. The obtained results show the merits of the proposed mathematical model, which makes the study of the interactions between various climatic factors possible.