Novel SNC-NN-MRAS Based Speed Estimator for Sensor-Less Vector Controlled IM Drives

Rotor Flux based Model Reference Adaptive System (RF-MRAS) is the most popularly used conventional speed estimation scheme for sensor-less IM drives. In this scheme, the voltage model equations are used for the reference model. This encounters major drawbacks at low frequencies/speed which leads to the poor performance of RF-MRAS. Replacing the reference model using Neural Network (NN) based flux estimator provides an alternate solution and addresses such drawbacks. This paper identifies an NN based flux estimator using Single Neuron Cascaded (SNC) Architecture. The proposed SNC-NN model replaces the conventional voltage model in RF-MRAS to form a novel MRAS scheme named as SNC-NN-MRAS. Through simulation the proposed SNC-NN-MRAS is shown to be promising in terms of all major issues and robustness to parameter variation. The suitability of the proposed SNC-NN-MRAS based speed estimator and its advantages over RF-MRAS for sensor-less induction motor drives is comprehensively presented through extensive simulations.

A Decision Support Tool for Evaluating Mobility Projects

Success is a European project that will implement several clean transport offers in three European cities and evaluate the environmental impacts. The goal of these measures is to improve urban mobility or the displacement of residents inside cities. For e.g. park and ride, electric vehicles, hybrid bus and bike sharing etc. A list of 28 criteria and 60 measures has been established for evaluation of these transport projects. The evaluation criteria can be grouped into: Transport, environment, social, economic and fuel consumption. This article proposes a decision support system based that encapsulates a hybrid approach based on fuzzy logic, multicriteria analysis and belief theory for the evaluation of impacts of urban mobility solutions. A web-based tool called DeSSIA (Decision Support System for Impacts Assessment) has been developed that treats complex data. The tool has several functionalities starting from data integration (import of data), evaluation of projects and finishes by graphical display of results. The tool development is based on the concept of MVC (Model, View, and Controller). The MVC is a conception model adapted to the creation of software's which impose separation between data, their treatment and presentation. Effort is laid on the ergonomic aspects of the application. It has codes compatible with the latest norms (XHTML, CSS) and has been validated by W3C (World Wide Web Consortium). The main ergonomic aspect focuses on the usability of the application, ease of learning and adoption. By the usage of technologies such as AJAX (XML and Java Script asynchrones), the application is more rapid and convivial. The positive points of our approach are that it treats heterogeneous data (qualitative, quantitative) from various information sources (human experts, survey, sensors, model etc.).

Use Cuticular Hydrocarbons as Chemotaxonomic of The Pamphagidae Pamphagus elephas (Insecta, Orthoptera) of Algeria

The cuticular hydrocarbons of Pamphagus elephas (Orthoptera: Pamphagidae) has been analysed by gas chromatography and by combined gas chromatograph-mass spectrometry. The following hydrocarbon classes have been identified in insect cuticular hydrocarbons are: n-alkanes and methylalkanes comprising Monomethyl-, dimethyl-and trimethylalkanes. Sexual dimorphism is observed in long chain alkanes (C24-C36) present on male and female. The cuticulars hydrocarbons of P.elephas ranged from 24 to 36 carbons and incluted n-alkanes, Dimethylalkanes and Trimethylalkanes. nalkanes represented by (C24-C36,72,7% on male and 79,2% on female), internally branched Monomethylalkanes identified were (C25, C30-C32,C35-C37;11% on male and 9,4% on female), Dimethylalkanes detected are (C31-C32, C36; 2,2% on male and 2,06% on female) and Trimethylalkanes detected are (C32, C36; 3,1% on male and 4, 97 on female). Larvae male and female (stage 7) showed the same quality of n-alkanes observed in adults. However a difference quantity is noted.

A Fuzzy Time Series Forecasting Model for Multi-Variate Forecasting Analysis with Fuzzy C-Means Clustering

In this study, a fuzzy integrated logical forecasting method (FILF) is extended for multi-variate systems by using a vector autoregressive model. Fuzzy time series forecasting (FTSF) method was recently introduced by Song and Chissom [1]-[2] after that Chen improved the FTSF method. Rather than the existing literature, the proposed model is not only compared with the previous FTS models, but also with the conventional time series methods such as the classical vector autoregressive model. The cluster optimization is based on the C-means clustering method. An empirical study is performed for the prediction of the chartering rates of a group of dry bulk cargo ships. The root mean squared error (RMSE) metric is used for the comparing of results of methods and the proposed method has superiority than both traditional FTS methods and also the classical time series methods.

Effect of Medium Capacity on the Relationship between Chemical Heterogeneity and Linearly Adsorbed Solute Dispersion into Fixed Beds

The paper aims at investigating influence of medium capacity on linear adsorbed solute dispersion into chemically heterogeneous fixed beds. A discrete chemical heterogeneity distribution is considered in the one-dimensional advectivedispersive equation. The partial differential equation is solved using finite volumes method based on the Adam-Bashforth algorithm. Increased dispersion is estimated by comparing breakthrough curves second order moments and keeping identical hydrodynamic properties. As a result, dispersion increase due to chemical heterogeneity depends on the column size and surprisingly on the solid capacity. The more intense capacity is, the more important solute dispersion is. Medium length which is known to favour this effect vanishing according to the linear adsorption in fixed bed seems to create nonmonotonous variation of dispersion because of the heterogeneity. This nonmonotonous behaviour is also favoured by high capacities.

Ant System with Acoustic Communication

Ant colony optimization is an ant algorithm framework that took inspiration from foraging behavior of ant colonies. Indeed, ACO algorithms use a chemical communication, represented by pheromone trails, to build good solutions. However, ants involve different communication channels to interact. Thus, this paper introduces the acoustic communication between ants while they are foraging. This process allows fine and local exploration of search space and permits optimal solution to be improved.

SOA and BPM Partnership: A Paradigm for Dynamic and Flexible Process and I.T. Management

Business Process Management (BPM) helps in optimizing the business processes inside an enterprise. But BPM architecture does not provide any help for extending the enterprise. Modern business environments and rapidly changing technologies are asking for brisk changes in the business processes. Service Oriented Architecture (SOA) can help in enabling the success of enterprise-wide BPM. SOA supports agility in software development that is directly related to achieve loose coupling of interacting software agents. Agility is a premium concern of the current software designing architectures. Together, BPM and SOA provide a perfect combination for enterprise computing. SOA provides the capabilities for services to be combined together and to support and create an agile, flexible enterprise. But there are still many questions to answer; BPM is better or SOA? and what is the future track of BPM and SOA? This paper tries to answer some of these important questions.

The Effect of Seed Inoculation (Pseudomonas putida+Bacillus lentus) and Different Levels of Fertilizers on Yield and Yield Components of Wheat (Triticum aestivum L.) Cultivars

In order to study of The Effect of seed inoculation with Pseudomonas putida+Bacillus lentus on yield and yield components of wheat (Triticum aestivum L.) cultivars, an experiment was carried out as factorial based on Randomized Complete Block Design (RCBD) in Agricultural Research Station of Shahrood University of Technology. Results showed that inoculation with Pseudomonas putida+Bacillus lentus promoted seed germination. Also, inoculation with Pseudomonas putida+Bacillus lentus significantly affected grain yield, Number of spikes per m2, Number of grain per spike and 1000-seed weight and There was not statistically significant difference between Chamran and Pishtaz cultivars . Finally, the dosages of chemical fertilizers currently applied in commercial wheat field in Iran (Shahrood region) could be reduced through proper combination of Pseudomonas putida+Bacillus lentus inoculation plus fertilization.

Difference in Psychological Well-Being Based On Comparison of Religions: A Case Study in Pekan District, Pahang, Malaysia

The psychological well-being of a family is a subjective matter for evaluation, all the more when it involves the element of religions, whether Islam, Christianity, Buddhism or Hinduism. Each of these religions emphasises similar values and morals on family psychological well-being. This comparative study is specifically to determine the role of religion on family psychological well-being in Pekan district, Pahang, Malaysia. The study adopts a quantitative and qualitative mixed method design and considers a total of 412 samples of parents and children for the quantitative study, and 21 samples for the qualitative study. The quantitative study uses simple random sampling, whereas the qualitative sampling is purposive. The instrument for quantitative study is Ryff’s Psychological Well-being Scale and the qualitative study involves the construction of a guidelines protocol for in-depth interviews of respondents. The quantitative study uses the SPSS version .19 with One Way Anova, and the qualitative analysis is manual based on transcripts with specific codes and themes. The results show nonsignificance, that is, no significant difference among religions in all family psychological well-being constructs in the comparison of Islam, Christianity, Buddhism and Hinduism, thereby accepting a null hypothesis and rejecting an alternative hypothesis. The qualitative study supports the quantitative study, that is, all 21 respondents explain that no difference exists in psychological wellbeing in the comparison of teachings in all the religious mentioned. These implications may be used as guidelines for government and non-government bodies in considering religion as an important element in family psychological well-being in the long run. 

Design of a Constant Chord Single-Rotating Propeller using Lock and Goldstein Techniques

Design of a constant chord propeller is presented in this paper in order to reduce propeller-s design procedure-s costs. The design process was based on Lock and Goldstein-s techniques of propeller design and analysis. In order to calculate optimum chord of propeller, chord of a referential element is generalized as whole blades chord. The design outcome which named CS-X-1 is modeled & analyzed by CFD methods using K-ε: R.N.G turbulence model. Convergence of results of two codes proved that outcome results of design process are reliable. Design result is a two-blade propeller with a total diameter of 1.1 meter, radial velocity of 3000 R.P.M, efficiency above .75 and power coefficient near 1.05.

Capacity and Performance Analysis of Space-Time Block Coded MIMO-OFDM Systems over Rician Fading Channel

This paper presents an analysis on the capacity and performance of MIMO-OFDM systems. The work is focused on the capacity of MIMO-OFDM systems over rician fading channel, in the case of the channel being known at the receiver only, which is more practical case of the channel. Simple expression for capacity is derived for the case of correlated rician fading. The performance of some MIMO-OFDM implementations with rician fading model is presented using an Alamouti coding scheme and Simulation results are obtained for both capacity and performance analysis.

Phase Transformation Temperatures for Shape Memory Alloy Wire

Phase transformation temperature is one of the most important parameters for the shape memory alloys (SMAs). The most popular method to determine these phase transformation temperatures is the Differential Scanning Calorimeter (DSC), but due to the limitation of the DSC testing itself, it made it difficult for the finished product which is not in the powder form. A novel method which uses the Universal Testing Machine has been conducted to determine the phase transformation temperatures. The Flexinol wire was applied with force and maintained throughout the experiment and at the same time it was heated up slowly until a temperature of approximately 1000C with direct current. The direct current was then slowly decreased to cool down the temperature of the Flexinol wire. All the phase transformation temperatures for Flexinol wire were obtained. The austenite start at 52.540C and austenite finish at 60.900C, while martensite start at 44.780C and martensite finish at 32.840C.

Effect of Anoxia on Root Growth and Grain Yield of Wheat Cultivars

Waterlogging reduces shoot and root growth and final yield of wheat. Waterlogged sites have a combination of low slope, high rainfall, heavy texture and low permeability. This study was aimed the importance of waterlogging on root growth and wheat yield. In order to study the effects of different waterlogging duration (0, 10, 20 and 30 days) at growth stages (1-leaf stage, tillering stage and stem elongation stage) on root growth of wheat cultivars (Chamran, Vee/Nac and Yavaroos), one pot experiment was carried out. The experiment was a factorial according to a RCBD with three replications. Results showed that root dry weight and total root length in the anthesis and grain ripening stages and biological and grain yields were significantly different between cultivars, growth stages and waterlogging durations. Vee/Nac was found superior with respect to other cultivars. Susceptibility to waterlogging at different growth stages for cultivars was 1-leaf stage > tillering stage > stem elongation stage. Under waterlogging treatments, grain and biological yields, were decreased 44.5 and 39.8%, respectively. Root length and root dry weight were reduced 55.1 and 45.2%, respectively, too. In this experiment, decrease at root growth because of waterlogging reduced grain and biological yields. Based on the results, even short period (10 days) of waterlogging had unrecoverable effects on the root growth and grain yield of wheat.

Extended Minimal Controller Synthesis for Voltage-Fed Induction Motor Based on the Hyperstability Theory

in this work, we present a new strategy of direct adaptive control denoted: Extended minimal controller synthesis (EMCS). This algorithm is designed for an induction motor, which includes both electrical and mechanical dynamics under the assumptions of linear magnetic circuits. The main motivation of the EMCS control is to enhance the robustness of the MRAC algorithms, i.e. the rejection of bounded effects of rapidly varying external disturbances.

Speed Sensorless Control with a Linearizationby State Feedback of Asynchronous Machine Using a Model Reference Adaptive System

In this paper, we show that the association of the PI regulators for the speed and stator currents with a control strategy using the linearization by state feedback for an induction machine without speed sensor, and with an adaptation of the rotor resistance. The rotor speed is estimated by using the model reference adaptive system approach (MRAS). This method consists of using two models: The first is the reference model and the second is an adjustable one in which two components of the stator flux, obtained from the measurement of the currents and stator voltages are estimated. The estimated rotor speed is then obtained by canceling the difference between stator-flux of the reference model and those of the adjustable one. Satisfactory results of simulation are obtained and discussed in this paper to highlight the proposed approach.

Dynamic Clustering Estimation of Tool Flank Wear in Turning Process using SVD Models of the Emitted Sound Signals

Monitoring the tool flank wear without affecting the throughput is considered as the prudent method in production technology. The examination has to be done without affecting the machining process. In this paper we proposed a novel work that is used to determine tool flank wear by observing the sound signals emitted during the turning process. The work-piece material we used here is steel and aluminum and the cutting insert was carbide material. Two different cutting speeds were used in this work. The feed rate and the cutting depth were constant whereas the flank wear was a variable. The emitted sound signal of a fresh tool (0 mm flank wear) a slightly worn tool (0.2 -0.25 mm flank wear) and a severely worn tool (0.4mm and above flank wear) during turning process were recorded separately using a high sensitive microphone. Analysis using Singular Value Decomposition was done on these sound signals to extract the feature sound components. Observation of the results showed that an increase in tool flank wear correlates with an increase in the values of SVD features produced out of the sound signals for both the materials. Hence it can be concluded that wear monitoring of tool flank during turning process using SVD features with the Fuzzy C means classification on the emitted sound signal is a potential and relatively simple method.

Speed Sensorless IFOC of PMSM Based On Adaptive Luenberger Observer

In this paper, Speed Sensorless Indirect Field Oriented Control (IFOC) of a Permanent Magnet Synchronous machine (PMSM) is studied. The closed loop scheme of the drive system utilizes fuzzy speed and current controllers. Due to the well known drawbacks of the speed sensor, an algorithm is proposed in this paper to eliminate it. In fact, based on the model of the PMSM, the stator currents and rotor speed are estimated simultaneously using adaptive Luenberger observer for currents and MRAS (Model Reference Adaptive System) observer for rotor speed. To overcome the sensivity of this algorithm against parameter variation, adaptive for on line stator resistance tuning is proposed. The validity of the proposed method is verified by an extensive simulation work.

Response of King Abdulla Canal Water to the Upgrade of As Samra WWTP

The response of King Abdulla Canal (KAC) water to the upgrade of As Samra Wastewater Treatment Plant which discharges its effluent to the Zarqa River is investigated. Time series quality data that extends between October 2005 and December 2009 obtained by a state of the art telemetric monitoring system were analyzed for COD, EC, TP and TN at two monitoring stations located upstream and downstream of the confluence of the Zarqa River with KAC. The samples- means and the t-test showed that there has been significant improvement in the quality of the KAC water for COD, and TP. However, the improvement in the TN was found statistically insignificant, whereas the EC of the KAC was unaffected by the upgrade. Comparing the selected parameters with the standards and guidelines for using treated wastewater in irrigation showed that the KAC water has improved towards meeting the required standards and guidelines for treated wastewater reuse in irrigation.

Motor Imaginary Signal Classification Using Adaptive Recursive Bandpass Filter and Adaptive Autoregressive Models for Brain Machine Interface Designs

The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.

The Evaluation and the Comparison of the Effect of Without Engine Power and Power Mechanical Systems on Rice Weed

In order to study the influence of different methods of controlling weeds such as mechanical weeding and mechanical weeder efficiency analysis in mechanical cultivation conditions, in farming year of 2011 an experiment was done in a farm in coupling and development of technology center in Haraz,Iran. The treatments consisted of (I) control treatment: where no weeding was done, (II) use of mechanical weeding without engine and (III) power mechanical weeding. Results showed that experimental treatments had significantly different effects (p=0.05) on yield traits and number of filled grains per panicle, while treatments had the significant effects on grain weight and dry weight of weeds in the first, second and third weeding methods at 1% of confidence level. Treatment (II) had its most significant effect on number of filled grains per panicle and yield performance standpoint, which was 3705.97 kg ha-1 in its highest peak. Treatment (III) was ranked as second influential with 3559.8 kg ha-1. In addition, under (I) treatments, 2364.73 kg ha-1 of yield produced. The minimum dry weights of weeds in all weeding methods were related to the treatment (II), (III) and (I), respectively. The correlation coefficient analysis showed that total yield had a significant positive correlation with the panicle grain yield per plant (r= 0.55*) and the number of grains per panicle-1 (r= 0.57*) and the number of filled grains (r= 0.63*). Total rice yield also had negative correlation of r= -0. 64* with weed dry weight at second weed sampling time (17 DAT). The weed dry weight at third and fourth sampling times (24 and 40 DAT) had negative correlations of -0.65** and r=-0.61* with rice yield, respectively.