Search results for: "Power system voltage control using lp and artificial neural network"
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14055

Search results for: "Power system voltage control using lp and artificial neural network"

13065 A Simulator for Robot Navigation Algorithms

Authors: Michael A. Folcik, Bijan Karimi

Abstract:

A robot simulator was developed to measure and investigate the performance of a robot navigation system based on the relative position of the robot with respect to random obstacles in any two dimensional environment. The presented simulator focuses on investigating the ability of a fuzzy-neural system for object avoidance. A navigation algorithm is proposed and used to allow random navigation of a robot among obstacles when the robot faces an obstacle in the environment. The main features of this simulator can be used for evaluating the performance of any system that can provide the position of the robot with respect to obstacles in the environment. This allows a robot developer to investigate and analyze the performance of a robot without implementing the physical robot.

Keywords: Applications of Fuzzy Logic and Neural Networksin Robotics, Artificial Intelligence, Embedded Systems, MobileRobots, Robot Navigation, Robotics.

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13064 Simulation and Realization of a Battery Charge Regulator

Authors: B. Nasri, M. Bensaada

Abstract:

We present a simulation and realization of a battery charge regulator (BCR) in microsatellite earth observation. The tests were performed on battery pack 12volt, capacity 24Ah and the solar array open circuit voltage of 100 volt and optimum power of about 250 watt. The battery charge is made by solar module. The principle is to adapt the output voltage of the solar module to the battery by using the technique of pulse width modulation (PWM). Among the different techniques of charge battery, we opted for the technique of the controller ON/OFF is a standard technique and simple, it-s easy to be board executed validation will be made by simulation "Proteus Isis Professional software ". The circuit and the program of this prototype are based on the PIC16F877 microcontroller, a serial interface connecting a PC is also realized, to view and save data and graphics in real time, for visualization of data and graphs we develop an interface tool “visual basic.net (VB)--.

Keywords: Battery Charge Regulator, Batteries, Buck converter, Power System, Power Conditioning, Power Distribution, Solar arrays.

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13063 Smart Grid Communication Architecture Modeling for Heterogeneous Network Based Advanced Metering Infrastructure

Authors: S. Prem Kumar, H. Thameemul Ansari, V. Saminadan

Abstract:

A smart grid is an emerging technology in the power delivery system which provides an intelligent, self-recovery and homeostatic grid in delivering power to the users. Smart grid communication network provides transmission capacity for information transformation within the connected nodes in the network, in favor of functional and operational needs. In the electric grids communication network delay is based on choosing the appropriate technology and the types of devices enforced. In distinction, the combination of IEEE 802.16 based WiMAX and IEEE 802.11 based WiFi technologies provides improved coverage and gives low delay performances to meet the smart grid needs. By incorporating this method in Wide Area Monitoring System (WAMS) and Advanced Metering Infrastructure (AMI) the performance of the smart grid will be considerably improved. This work deals with the implementation of WiMAX-WLAN integrated network architecture for WAMS and AMI in the smart grid.

Keywords: WiMAX, WLAN, WAMS, Smart Grid, HetNet, AMI.

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13062 Electrical Analysis of Corn Oil as an Alternative to Mineral Oil in Power Transformers

Authors: E. Taslak, C. Kocatepe, O. Arıkan, C. F. Kumru

Abstract:

In insulation and cooling of power transformers various liquids are used. Mineral oils have wide availability and low cost. However, they have a poor biodegradability potential and lower fire point in comparison with other insulating liquids. Use of a liquid having high biodegradability is important due to environmental consideration. This paper investigates edible corn oil as an alternative to mineral oil. Various properties of mineral and corn oil like breakdown voltage, dissipation factor, relative dielectric constant, power loss and resistivity were measured according to different standards.

Keywords: Breakdown voltage, corn oil, dissipation factor, mineral oil, power loss, relative dielectric constant, resistivity.

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13061 Evaluation of Optimal Transfer Capability in Power System Interconnection

Authors: Jin-O Kim, Hyun-Il Son

Abstract:

As the electrical power industry is restructured, the electrical power exchange is becoming extended. One of the key information used to determine how much power can be transferred through the network is known as available transfer capability (ATC). To calculate ATC, traditional deterministic approach is based on the severest case, but the approach has the complexity of procedure. Therefore, novel approach for ATC calculation is proposed using cost-optimization method in this paper, and is compared with well-being method and risk-benefit method. This paper proposes the optimal transfer capability of HVDC system between mainland and a separated island in Korea through these three methods. These methods will consider production cost, wheeling charge through HVDC system and outage cost with one depth (N-1 contingency)

Keywords: ATC, power system interconnection, well-being method, cost-optimization method, risk-benefit analysis, outage cost.

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13060 GSM-Based Approach for Indoor Localization

Authors: M.Stella, M. Russo, D. Begušić

Abstract:

Ability of accurate and reliable location estimation in indoor environment is the key issue in developing great number of context aware applications and Location Based Services (LBS). Today, the most viable solution for localization is the Received Signal Strength (RSS) fingerprinting based approach using wireless local area network (WLAN). This paper presents two RSS fingerprinting based approaches – first we employ widely used WLAN based positioning as a reference system and then investigate the possibility of using GSM signals for positioning. To compare them, we developed a positioning system in real world environment, where realistic RSS measurements were collected. Multi-Layer Perceptron (MLP) neural network was used as the approximation function that maps RSS fingerprints and locations. Experimental results indicate advantage of WLAN based approach in the sense of lower localization error compared to GSM based approach, but GSM signal coverage by far outreaches WLAN coverage and for some LBS services requiring less precise accuracy our results indicate that GSM positioning can also be a viable solution.

Keywords: Indoor positioning, WLAN, GSM, RSS, location fingerprints, neural network.

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13059 PID Control Design Based on Genetic Algorithm with Integrator Anti-Windup for Automatic Voltage Regulator and Speed Governor of Brushless Synchronous Generator

Authors: O. S. Ebrahim, M. A. Badr, Kh. H. Gharib, H. K. Temraz

Abstract:

This paper presents a methodology based on genetic algorithm (GA) to tune the parameters of proportional-integral-differential (PID) controllers utilized in the automatic voltage regulator (AVR) and speed governor of a brushless synchronous generator driven by three-stage steam turbine. The parameter tuning is represented as a nonlinear optimization problem solved by GA to minimize the integral of absolute error (IAE). The problem of integral windup due to physical system limitations is solved using simple anti-windup scheme. The obtained controllers are compared to those designed using classical Ziegler-Nichols technique and constrained optimization. Results show distinct superiority of the proposed method.

Keywords: Brushless synchronous generator, Genetic Algorithm, GA, Proportional-Integral-Differential control, PID control, automatic voltage regulator, AVR.

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13058 Wear Measuring and Wear Modelling Based On Archard, ASTM, and Neural Network Models

Authors: A. Shebani, C. Pislaru

Abstract:

The wear measuring and wear modelling are fundamental issues in the industrial field, mainly correlated to the economy and safety. Therefore, there is a need to study the wear measurements and wear estimation. Pin-on-disc test is the most common test which is used to study the wear behaviour. In this paper, the pin-on-disc (AEROTECH UNIDEX 11) is used for the investigation of the effects of normal load and hardness of material on the wear under dry and sliding conditions. In the pin-on-disc rig, two specimens were used; one, a pin is made of steel with a tip, positioned perpendicular to the disc, where the disc is made of aluminium. The pin wear and disc wear were measured by using the following instruments: The Talysurf instrument, a digital microscope, and the alicona instrument. The Talysurf profilometer was used to measure the pin/disc wear scar depth, digital microscope was used to measure the diameter and width of wear scar, and the alicona was used to measure the pin wear and disc wear. After that, the Archard model, American Society for Testing and Materials model (ASTM), and neural network model were used for pin/disc wear modelling. Simulation results were implemented by using the Matlab program. This paper focuses on how the alicona can be used for wear measurements and how the neural network can be used for wear estimation.

Keywords: Wear measuring, Wear modelling, Neural Network, Alicona.

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13057 Concept, Design and Implementation of Power System Component Simulator Based on Thyristor Controlled Transformer and Power Converter

Authors: B. Kędra, R. Małkowski

Abstract:

This paper presents information on Power System Component Simulator – a device designed for LINTE^2 laboratory owned by Gdansk University of Technology in Poland. In this paper, we first provide an introductory information on the Power System Component Simulator and its capabilities. Then, the concept of the unit is presented. Requirements for the unit are described as well as proposed and introduced functions are listed. Implementation details are given. Hardware structure is presented and described. Information about used communication interface, data maintenance and storage solution, as well as used Simulink real-time features are presented. List and description of all measurements is provided. Potential of laboratory setup modifications is evaluated. Lastly, the results of experiments performed using Power System Component Simulator are presented. This includes simulation of under frequency load shedding, frequency and voltage dependent characteristics of groups of load units, time characteristics of group of different load units in a chosen area.

Keywords: Power converter, Simulink real-time, MATLAB, load, tap controller.

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13056 Earth Grid Safety Consideration: Civil Upgrade Works for an Energised Substation

Authors: M. Nassereddine, A. Hellany, M. Nagrial, J. Rizk

Abstract:

The demand on High voltage (HV) infrastructures is growing due to the corresponding growth in industries and population. Many areas are being developed and therefore require additional electrical power to comply with the demand. Substation upgrade is one of the rapid solutions to ensure the continuous supply of power to customers. This upgrade requires civil modifications to structures and fences. The civil work requires excavation and steel works that may create unsafe touch conditions. This paper presents a brief theoretical overview of the touch voltage inside and around substations and uses CDEGS software to simulate a case study.

Keywords: Earth safety, High Voltage, AC interference, Earthing Design.

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13055 Dynamic Measurement System Modeling with Machine Learning Algorithms

Authors: Changqiao Wu, Guoqing Ding, Xin Chen

Abstract:

In this paper, ways of modeling dynamic measurement systems are discussed. Specially, for linear system with single-input single-output, it could be modeled with shallow neural network. Then, gradient based optimization algorithms are used for searching the proper coefficients. Besides, method with normal equation and second order gradient descent are proposed to accelerate the modeling process, and ways of better gradient estimation are discussed. It shows that the mathematical essence of the learning objective is maximum likelihood with noises under Gaussian distribution. For conventional gradient descent, the mini-batch learning and gradient with momentum contribute to faster convergence and enhance model ability. Lastly, experimental results proved the effectiveness of second order gradient descent algorithm, and indicated that optimization with normal equation was the most suitable for linear dynamic models.

Keywords: Dynamic system modeling, neural network, normal equation, second order gradient descent.

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13054 Artificial Neural Network Modeling and Genetic Algorithm Based Optimization of Hydraulic Design Related to Seepage under Concrete Gravity Dams on Permeable Soils

Authors: Muqdad Al-Juboori, Bithin Datta

Abstract:

Hydraulic structures such as gravity dams are classified as essential structures, and have the vital role in providing strong and safe water resource management. Three major aspects must be considered to achieve an effective design of such a structure: 1) The building cost, 2) safety, and 3) accurate analysis of seepage characteristics. Due to the complexity and non-linearity relationships of the seepage process, many approximation theories have been developed; however, the application of these theories results in noticeable errors. The analytical solution, which includes the difficult conformal mapping procedure, could be applied for a simple and symmetrical problem only. Therefore, the objectives of this paper are to: 1) develop a surrogate model based on numerical simulated data using SEEPW software to approximately simulate seepage process related to a hydraulic structure, 2) develop and solve a linked simulation-optimization model based on the developed surrogate model to describe the seepage occurring under a concrete gravity dam, in order to obtain optimum and safe design at minimum cost. The result shows that the linked simulation-optimization model provides an efficient and optimum design of concrete gravity dams.

Keywords: Artificial neural network, concrete gravity dam, genetic algorithm, seepage analysis.

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13053 Adaptive Pulse Coupled Neural Network Parameters for Image Segmentation

Authors: Thejaswi H. Raya, Vineetha Bettaiah, Heggere S. Ranganath

Abstract:

For over a decade, the Pulse Coupled Neural Network (PCNN) based algorithms have been successfully used in image interpretation applications including image segmentation. There are several versions of the PCNN based image segmentation methods, and the segmentation accuracy of all of them is very sensitive to the values of the network parameters. Most methods treat PCNN parameters like linking coefficient and primary firing threshold as global parameters, and determine them by trial-and-error. The automatic determination of appropriate values for linking coefficient, and primary firing threshold is a challenging problem and deserves further research. This paper presents a method for obtaining global as well as local values for the linking coefficient and the primary firing threshold for neurons directly from the image statistics. Extensive simulation results show that the proposed approach achieves excellent segmentation accuracy comparable to the best accuracy obtainable by trial-and-error for a variety of images.

Keywords: Automatic Selection of PCNN Parameters, Image Segmentation, Neural Networks, Pulse Coupled Neural Network

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13052 Prediction of Bath Temperature Using Neural Networks

Authors: H. Meradi, S. Bouhouche, M. Lahreche

Abstract:

In this work, we consider an application of neural networks in LD converter. Application of this approach assumes a reliable prediction of steel temperature and reduces a reblow ratio in steel work. It has been applied a conventional model to charge calculation, the obtained results by this technique are not always good, this is due to the process complexity. Difficulties are mainly generated by the noisy measurement and the process non linearities. Artificial Neural Networks (ANNs) have become a powerful tool for these complex applications. It is used a backpropagation algorithm to learn the neural nets. (ANNs) is used to predict the steel bath temperature in oxygen converter process for the end condition. This model has 11 inputs process variables and one output. The model was tested in steel work, the obtained results by neural approach are better than the conventional model.

Keywords: LD converter, bath temperature, neural networks.

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13051 Closely Parametrical Model for an Electrical Arc Furnace

Authors: Labar Hocine, Dgeghader Yacine, Kelaiaia Mounia Samira, Bounaya Kamel

Abstract:

To maximise furnace production it-s necessary to optimise furnace control, with the objectives of achieving maximum power input into the melting process, minimum network distortion and power-off time, without compromise on quality and safety. This can be achieved with on the one hand by an appropriate electrode control and on the other hand by a minimum of AC transformer switching. Electrical arc is a stochastic process; witch is the principal cause of power quality problems, including voltages dips, harmonic distortion, unbalance loads and flicker. So it is difficult to make an appropriate model for an Electrical Arc Furnace (EAF). The factors that effect EAF operation are the melting or refining materials, melting stage, electrode position (arc length), electrode arm control and short circuit power of the feeder. So arc voltages, current and power are defined as a nonlinear function of the arc length. In this article we propose our own empirical function of the EAF and model, for the mean stages of the melting process, thanks to the measurements in the steel factory.

Keywords: Modelling, electrical arc, melting, power, EAF, steel.

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13050 Modeling of Reusability of Object Oriented Software System

Authors: Parvinder S. Sandhu, Harpreet Kaur, Amanpreet Singh

Abstract:

Automatic reusability appraisal is helpful in evaluating the quality of developed or developing reusable software components and in identification of reusable components from existing legacy systems; that can save cost of developing the software from scratch. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. In this research work, structural attributes of software components are explored using software metrics and quality of the software is inferred by different Neural Network based approaches, taking the metric values as input. The calculated reusability value enables to identify a good quality code automatically. It is found that the reusability value determined is close to the manual analysis used to be performed by the programmers or repository managers. So, the developed system can be used to enhance the productivity and quality of software development.

Keywords: Neural Network, Software Reusability, Software Metric, Accuracy, MAE, RMSE.

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13049 A Novel Approach to EMABS and Comparison with ABS

Authors: Mehrdad N. Khajavi, Abbas Hosseini, N.Bani Mostafa

Abstract:

In this paper two different Antilock braking system (ABS) are simulated and compared. One is the ordinary hydraulic ABS system which we call it ABS and the other is Electromagnetic Antilock braking system which is called (EMABS) the basis of performance of an EMABS is based upon Electromagnetic force. In this system there is no need to use servo hydraulic booster which are used in ABS system. In EMABS to generate the desired force we have use a magnetic relay which works with an input voltage through an air gap (g). The generated force will be amplified by the relay arm, and is applied to the brake shoes and thus the braking torque is generated. The braking torque is proportional to the applied electrical voltage E. to adjust the braking torque it is only necessary to regulate the electrical voltage E which is very faster and has a much smaller time constant T than the ABS system. The simulations of these two different ABS systems are done with MATLAB/SIMULINK software and the superiority of the EMABS has been shown.

Keywords: ABS, EMABS, ECU

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13048 Distributed System Computing Resource Scheduling Algorithm Based on Deep Reinforcement Learning

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling. The research proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling. The paper concludes the challenges and improvement directions for Deep Reinforcement Learning-based resource scheduling algorithms.

Keywords: Resource scheduling, deep reinforcement learning, distributed system, artificial intelligence.

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13047 A Convolutional Neural Network-Based Vehicle Theft Detection, Location, and Reporting System

Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

Abstract:

One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets, especially in the motorist sector, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of Python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. 60 vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes that the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: Convolutional Neural Network, CNN, location identification, tracking, GPS, GSM.

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13046 Stability Enhancement of a Large-Scale Power System Using Power System Stabilizer Based on Adaptive Neuro Fuzzy Inference System

Authors: Agung Budi Muljono, I Made Ginarsa, I Made Ari Nrartha

Abstract:

A large-scale power system (LSPS) consists of two or more sub-systems connected by inter-connecting transmission. Loading pattern on an LSPS always changes from time to time and varies depend on consumer need. The serious instability problem is appeared in an LSPS due to load fluctuation in all of the bus. Adaptive neuro-fuzzy inference system (ANFIS)-based power system stabilizer (PSS) is presented to cover the stability problem and to enhance the stability of an LSPS. The ANFIS control is presented because the ANFIS control is more effective than Mamdani fuzzy control in the computation aspect. Simulation results show that the presented PSS is able to maintain the stability by decreasing peak overshoot to the value of −2.56 × 10−5 pu for rotor speed deviation Δω2−3. The presented PSS also makes the settling time to achieve at 3.78 s on local mode oscillation. Furthermore, the presented PSS is able to improve the peak overshoot and settling time of Δω3−9 to the value of −0.868 × 10−5 pu and at the time of 3.50 s for inter-area oscillation.

Keywords: ANFIS, large-scale, power system, PSS, stability enhancement.

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13045 A Model for Analysis the Induced Voltage of 115 kV On-Line Acting on Neighboring 22 kV Off-Line

Authors: S. Woothipatanapan, S. Prakobkit

Abstract:

This paper presents a model for analysis the induced voltage of transmission lines (energized) acting on neighboring distribution lines (de-energized). From environmental restrictions, 22 kV distribution lines need to be installed under 115 kV transmission lines. With the installation of the two parallel circuits like this, they make the induced voltage which can cause harm to operators. This work was performed with the ATP-EMTP modeling to analyze such phenomenon before field testing. Simulation results are used to find solutions to prevent danger to operators who are on the pole.

Keywords: Transmission system, distribution system, induced voltage, off-line operation.

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13044 Optimal Space Vector Control for Permanent Magnet Synchronous Motor based on Nonrecursive Riccati Equation

Authors: Marian Gaiceanu, Emil Rosu

Abstract:

In this paper the optimal control strategy for Permanent Magnet Synchronous Motor (PMSM) based drive system is presented. The designed full optimal control is available for speed operating range up to base speed. The optimal voltage space-vector assures input energy reduction and stator loss minimization, maintaining the output energy in the same limits with the conventional PMSM electrical drive. The optimal control with three components is based on the energetically criteria and it is applicable in numerical version, being a nonrecursive solution. The simulation results confirm the increased efficiency of the optimal PMSM drive. The properties of the optimal voltage space vector are shown.

Keywords: Matlab/Simulink, optimal control, permanent magnet synchronous motor, Riccati equation, space vector PWM

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13043 Design and Analysis of a Low Power High Speed 1 Bit Full Adder Cell Based On TSPC Logic with Multi-Threshold CMOS

Authors: Ankit Mitra

Abstract:

An adder is one of the most integral component of a digital system like a digital signal processor or a microprocessor. Being an extremely computationally intensive part of a system, the optimization for speed and power consumption of the adder is of prime importance. In this paper we have designed a 1 bit full adder cell based on dynamic TSPC logic to achieve high speed operation. A high threshold voltage sleep transistor is used to reduce the static power dissipation in standby mode. The circuit is designed and simulated in TSPICE using TSMC 180nm CMOS process. Average power consumption, delay and power-delay product is measured which showed considerable improvement in performance over the existing full adder designs.

Keywords: CMOS, TSPC, MTCMOS, ALU, Clock gating, power gating, pipelining.

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13042 A High-Speed and Low-Energy Ternary Content Addressable Memory Design Using Feedback in Match-Line Sense Amplifier

Authors: Syed Iftekhar Ali, M. S. Islam

Abstract:

In this paper we present an energy efficient match-line (ML) sensing scheme for high-speed ternary content-addressable memory (TCAM). The proposed scheme isolates the sensing unit of the sense amplifier from the large and variable ML capacitance. It employs feedback in the sense amplifier to successfully detect a match while keeping the ML voltage swing low. This reduced voltage swing results in large energy saving. Simulation performed using 130nm 1.2V CMOS logic shows at least 30% total energy saving in our scheme compared to popular current race (CR) scheme for similar search speed. In terms of speed, dynamic energy, peak power consumption and transistor count our scheme also shows better performance than mismatch-dependant (MD) power allocation technique which also employs feedback in the sense amplifier. Additionally, the implementation of our scheme is simpler than CR or MD scheme because of absence of analog control voltage and programmable delay circuit as have been used in those schemes.

Keywords: content-addressable memory, energy consumption, feedback, peak power, sensing scheme, sense amplifier, ternary.

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13041 Self-Tuning Power System Stabilizer Based on Recursive Least Square Identification and Linear Quadratic Regulator

Authors: J. Ritonja

Abstract:

Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.

Keywords: Adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification.

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13040 Power Quality Improvement Using PI and Fuzzy Logic Controllers Based Shunt Active Filter

Authors: Dipen A. Mistry, Bhupelly Dheeraj, Ravit Gautam, Manmohan Singh Meena, Suresh Mikkili

Abstract:

In recent years the large scale use of the power electronic equipment has led to an increase of harmonics in the power system. The harmonics results into a poor power quality and have great adverse economical impact on the utilities and customers. Current harmonics are one of the most common power quality problems and are usually resolved by using shunt active filter (SHAF). The main objective of this work is to develop PI and Fuzzy logic controllers (FLC) to analyze the performance of Shunt Active Filter for mitigating current harmonics under balanced and unbalanced sinusoidal source voltage conditions for normal load and increased load. When the supply voltages are ideal (balanced), both PI and FLC are converging to the same compensation characteristics. However, the supply voltages are non-ideal (unbalanced), FLC offers outstanding results. Simulation results validate the superiority of FLC with triangular membership function over the PI controller.

Keywords: DC link voltage, Fuzzy logic controller, Harmonics, PI controller, Shunt Active Filter.

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13039 Migration and Accumulation of Artificial Radionuclides in the System Water-Soil-Plants Depending on Polymers Applying

Authors: Anna H. Tadevosyan, Stepan K. Mayrapetyan, Michael P. Schellenberg, Laura M. Ghalachyan, Albert H. Hovsepyan, Khachatur S. Mayrapetyan

Abstract:

The possibility of radionuclides-related contamination of lands at agricultural holdings defines the necessity to apply special protective measures in plant growing. The aim of researches is to elucidate the influence of polymers applying on biological migration of man-made anthropogenic radionuclides 90Sr and 137Cs in the system water - soil – plant. The tests are being carried out under field conditions with and without application of polymers in root-inhabited media in more radioecological tension zone (with the radius of 7 km from the Armenian Nuclear Power Plant). The polymers on the base of K+, Caµ, KµCaµ ions were tested. Productivity of pepper depending on the presence and type of polymer material, content of artificial radionuclides in waters, soil and plant material has been determined. The character of different polymers influence on the artificial radionuclides migration and accumulation in the system water-soil-plant and accumulation in the plants has been cleared up.

Keywords: accumulation of artificial radionuclides, pepper, polymer, water-soil-plant system

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13038 Development of a Spark Electrode Ignition System for an Explosion Vessel

Authors: Shaharin A. Sulaiman, Mizuan Minhat

Abstract:

This paper presents development of an ignition system using spark electrodes for application in a research explosion vessel. A single spark is aimed to be discharged with quantifiable ignition energy. The spark electrode system would enable study of flame propagation, ignitability of fuel-air mixtures and other fundamental characteristics of flames. The principle of the capacitive spark circuit of ASTM is studied to charge an appropriate capacitance connected across the spark gap through a large resistor by a high voltage from the source of power supply until the initiation of spark. Different spark energies could be obtained mainly by varying the value of the capacitance and the supply current. The spark sizes produced are found to be affected by the spark gap, electrode size, input voltage and capacitance value.

Keywords: Ignition, Spark Electrode, Flame

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13037 Word Recognition and Learning based on Associative Memories and Hidden Markov Models

Authors: Zöhre Kara Kayikci, Günther Palm

Abstract:

A word recognition architecture based on a network of neural associative memories and hidden Markov models has been developed. The input stream, composed of subword-units like wordinternal triphones consisting of diphones and triphones, is provided to the network of neural associative memories by hidden Markov models. The word recognition network derives words from this input stream. The architecture has the ability to handle ambiguities on subword-unit level and is also able to add new words to the vocabulary during performance. The architecture is implemented to perform the word recognition task in a language processing system for understanding simple command sentences like “bot show apple".

Keywords: Hebbian learning, hidden Markov models, neuralassociative memories, word recognition.

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13036 SCR-Based Advanced ESD Protection Device for Low Voltage Application

Authors: Bo Bae Song, Byung Seok Lee, Hyun Young Kim, Chung Kwang Lee, Yong Seo Koo

Abstract:

This paper proposed a silicon controller rectifier (SCR) based ESD protection device to protect low voltage ESD for integrated circuit. The proposed ESD protection device has low trigger voltage and high holding voltage compared with conventional SCR-based ESD protection devices. The proposed ESD protection circuit is verified and compared by TCAD simulation. This paper verified effective low voltage ESD characteristics with low trigger voltage of 5.79V and high holding voltage of 3.5V through optimization depending on design variables (D1, D2, D3 and D4).

Keywords: ESD, SCR, Holding voltage, Latch-up.

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