Search results for: "Power system voltage control using lp and artificial neural network"
12438 A Multi-Feature Deep Learning Algorithm for Urban Traffic Classification with Limited Labeled Data
Authors: Rohan Putatunda, Aryya Gangopadhyay
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Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).
Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43212437 Self-Organizing Control Systems for Unstable and Deterministic Chaotic Processes
Authors: M. A. Beisenbi, N. M. Kissikova, S. E. Beisembina, S. T. Suleimenova, S. A. Kaliyeva
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The paper proposes a method for constructing a self-organizing control system for unstable and deterministic chaotic processes in the class of catastrophe “hyperbolic umbilic” for objects with m-inputs and n-outputs. The self-organizing control system is investigated by the universal gradient-velocity method of Lyapunov vector-functions. The conditions for self-organization of the control system in the class of catastrophes “hyperbolic umbilic” are shown in the form of a system of algebraic inequalities that characterize the aperiodic robust stability in the stationary states of the system.
Keywords: Gradient-velocity method of Lyapunov vector-functions, hyperbolic umbilic, self-organizing control system, stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 46112436 An Energy Efficient Digital Baseband for Batteryless Remote Control
Authors: Wei-Da Toh, Yuan Gao, Minkyu Je
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In this paper, an energy efficient digital baseband circuit for piezoelectric (PE) harvester powered batteryless remote control system is presented. Pulse mode PE harvester, which provides short duration of energy, is adopted to replace conventional chemical battery in wireless remote controller. The transmitter digital baseband repeats the control command transmission once the digital circuit is initiated by the power-on-reset. A power efficient data frame format is proposed to maximize the transmission repetition time. By using the proposed frame format and receiver clock and data recovery method, the receiver baseband is able to decode the command even when the received data has 20% error. The proposed transmitter and receiver baseband are implemented using FPGA and simulation results are presented.
Keywords: Clock and Data Recovery (CDR), Correlator, Digital Baseband, Gold Code, Power-On-Reset.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 202312435 On-Road Text Detection Platform for Driver Assistance Systems
Authors: Guezouli Larbi, Belkacem Soundes
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The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered as a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.
Keywords: Text detection, CNN, PZM, deep learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16312434 Performance Analysis of an Island Power System Including Wind Turbines Operating under Random Wind Speed
Authors: Meng-Jen Chen, Yu-Chi Wu, Guo-Tsai Liu, Sen-Feng Lin
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With continuous rise of oil price, how to develop alternative energy source has become a hot topic around the world. This study discussed the dynamic characteristics of an island power system operating under random wind speed lower than nominal wind speeds of wind turbines. The system primarily consists of three diesel engine power generation systems, three constant-speed variable-pitch wind turbines, a small hydraulic induction generation system, and lumped static loads. Detailed models based on Matlab/Simulink were developed to cater for the dynamic behavior of the system. The results suggested this island power system can operate stably in this operational mode. This study can serve as an important reference for planning, operation, and further expansion of island power systems.
Keywords: Diesel engine power generation system, constant-speed variable-pitch wind turbine, small hydraulic induction generation system, penetration, Matlab/Simulink, SimPowerSystems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 226012433 Implicit Lyapunov Control of Multi-Control Hamiltonians Systems Based On the State Error
Authors: Fangfang Meng, Shuang Cong
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In the closed quantum system, if the control system is strongly regular and all other eigenstates are directly coupled to the target state, the control system can be asymptotically stabilized at the target eigenstate by the Lyapunov control based on the state error. However, if the control system is not strongly regular or as long as there is one eigenstate not directly coupled to the target state, the situations will become complicated. In this paper, we propose an implicit Lyapunov control method based on the state error to solve the convergence problems for these two degenerate cases. And at the same time, we expand the target state from the eigenstate to the arbitrary pure state. Especially, the proposed method is also applicable in the control system with multi-control Hamiltonians. On this basis, the convergence of the control systems is analyzed using the LaSalle invariance principle. Furthermore, the relation between the implicit Lyapunov functions of the state distance and the state error is investigated. Finally, numerical simulations are carried out to verify the effectiveness of the proposed implicit Lyapunov control method. The comparisons of the control effect using the implicit Lyapunov control method based on the state distance with that of the state error are given.
Keywords: Implicit Lyapunov control, state error, degenerate cases, convergence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 150212432 Wind Farm Power Performance Verification Using Non-Parametric Statistical Inference
Authors: M. Celeska, K. Najdenkoski, V. Dimchev, V. Stoilkov
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Accurate determination of wind turbine performance is necessary for economic operation of a wind farm. At present, the procedure to carry out the power performance verification of wind turbines is based on a standard of the International Electrotechnical Commission (IEC). In this paper, nonparametric statistical inference is applied to designing a simple, inexpensive method of verifying the power performance of a wind turbine. A statistical test is explained, examined, and the adequacy is tested over real data. The methods use the information that is collected by the SCADA system (Supervisory Control and Data Acquisition) from the sensors embedded in the wind turbines in order to carry out the power performance verification of a wind farm. The study has used data on the monthly output of wind farm in the Republic of Macedonia, and the time measuring interval was from January 1, 2016, to December 31, 2016. At the end, it is concluded whether the power performance of a wind turbine differed significantly from what would be expected. The results of the implementation of the proposed methods showed that the power performance of the specific wind farm under assessment was acceptable.
Keywords: Canonical correlation analysis, power curve, power performance, wind energy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 103612431 An Intelligent Approach for Management of Hybrid DG System
Authors: Ali Vaseghi Ardekani, Hamid Reza Forutan, Amir Habibi, Ali Reza Rajabi, Hasan Adloo
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Distributed generation units (DGs) are grid-connected or stand-alone electric generation units located within the electric distribution system at or near the end user. It is generally accepted that centralized electric power plants will remain the major source of the electric power supply for the near future. DGs, however, can complement central power by providing incremental capacity to the utility grid or to an end user. This paper presents an efficient power dispatching model for hybrid wind-Solar power generation system, to satisfy some essential requirements, such as dispersed electric power demand, electric power quality and reducing generation cost and so on. In this paper, presented some elements of the main parts in the hybrid system; and then made fundamental dispatching strategies according to different situations; then pointed out four improving measures to improve genetic algorithm, such as: modify the producing way of selection probability, improve the way of crossover, protect excellent chromosomes, and change mutation range and so on. Finally, propose a technique for solving the unit's commitment for dispatching problem based on an improved genetic algorithm.
Keywords: Power Quality, Wind-Solar System, Genetic Algorithm, Hybrid System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 164612430 Significant Role Analysis of Transmission Control Protocols in 4G Cellular Systems
Authors: Ghassan A. Abed, Bayan M. Sabbar
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The society of 3rd Generation Partnership Project (3GPP) is completed developing Long Term Evolution Advanced (LTE-Advanced) systems as a standard 4G cellular system. This generation goals to produce conditions for a new radio-access technology geared to higher data rates, low latency, and better spectral efficiency. LTE-Advanced is an evolutionary step in the continuing development of LTE where the description in this article is based on LTE release 10. This paper provides a model of the traffic links of 4G system represented by LTE-Advanced system with the effect of the Transmission Control Protocols (TCP) and Stream Control Transmission Protocol (SCTP) in term of throughput and packet loss. Furthermore, the article presents the investigation and the analysis the behavior of SCTP and TCP variants over the 4G cellular systems. The traffic model and the scenario of the simulation developed using the network simulator NS-2 using different TCP source variants.
Keywords: LTE-Advanced, LTE, SCTP, TCP, 4G, NS-2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 194512429 Cooperative Sensing for Wireless Sensor Networks
Authors: Julien Romieux, Fabio Verdicchio
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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.Keywords: Cooperative signal processing, power management, signal representation, signal approximation, wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 178612428 Using Technology with a New Model of Management Development by Simulation of Neural Network and its Application on Intelligent Schools
Authors: Ahmad Ghayoumi, Mehdi Ghayoumi
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Intelligent schools are those which use IT devices and technologies as media software, hardware and networks to improve learning process. On the other hand management improvement is best described as the process from which managers learn and improve their skills not only to benefit themselves but also their employing organizations Here, we present a model Management improvement System that has been applied on some schools and have made strict improvement.Keywords: Intelligent school, Management development system, Learning station, Teaching station
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 109512427 Dynamic Admission Control for Quality of Service in IP Networks
Authors: J. Kasigwa, V. Baryamureeba, D. Williams
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The goal of admission control is to support the Quality of Service demands of real-time applications via resource reservation in IP networks. In this paper we introduce a novel Dynamic Admission Control (DAC) mechanism for IP networks. The DAC dynamically allocates network resources using the previous network pattern for each path and uses the dynamic admission algorithm to improve bandwidth utilization using bandwidth brokers. We evaluate the performance of the proposed mechanism through trace-driven simulation experiments in view point of blocking probability, throughput and normalized utilization.Keywords: Bandwidth broker, dynamic admission control(DAC), IP networks, quality of service, real-time flows.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 129512426 Modification of Electrical and Switching Characteristics of a Non Punch-Through Insulated Gate Bipolar Transistor by Gamma Irradiation
Authors: Hani Baek, Gwang Min Sun, Chansun Shin, Sung Ho Ahn
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Fast neutron irradiation using nuclear reactors is an effective method to improve switching loss and short circuit durability of power semiconductor (insulated gate bipolar transistors (IGBT) and insulated gate transistors (IGT), etc.). However, not only fast neutrons but also thermal neutrons, epithermal neutrons and gamma exist in the nuclear reactor. And the electrical properties of the IGBT may be deteriorated by the irradiation of gamma. Gamma irradiation damages are known to be caused by Total Ionizing Dose (TID) effect and Single Event Effect (SEE), Displacement Damage. Especially, the TID effect deteriorated the electrical properties such as leakage current and threshold voltage of a power semiconductor. This work can confirm the effect of the gamma irradiation on the electrical properties of 600 V NPT-IGBT. Irradiation of gamma forms lattice defects in the gate oxide and Si-SiO2 interface of the IGBT. It was confirmed that this lattice defect acts on the center of the trap and affects the threshold voltage, thereby negatively shifted the threshold voltage according to TID. In addition to the change in the carrier mobility, the conductivity modulation decreases in the n-drift region, indicating a negative influence that the forward voltage drop decreases. The turn-off delay time of the device before irradiation was 212 ns. Those of 2.5, 10, 30, 70 and 100 kRad(Si) were 225, 258, 311, 328, and 350 ns, respectively. The gamma irradiation increased the turn-off delay time of the IGBT by approximately 65%, and the switching characteristics deteriorated.Keywords: NPT-IGBT, gamma irradiation, switching, turn-off delay time, recombination, trap center.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 87312425 Comparative Study of IC and Perturb and Observe Method of MPPT Algorithm for Grid Connected PV Module
Authors: Arvind Kumar, Manoj Kumar, Dattatraya H. Nagaraj, Amanpreet Singh, Jayanthi Prattapati
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The purpose of this paper is to study and compare two maximum power point tracking (MPPT) algorithms in a photovoltaic simulation system and also show a simulation study of maximum power point tracking (MPPT) for photovoltaic systems using perturb and observe algorithm and Incremental conductance algorithm. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximize the power output from a PV system for a given set of conditions, and therefore maximize the array efficiency and minimize the overall system cost. Since the maximum power point (MPP) varies, based on the irradiation and cell temperature, appropriate algorithms must be utilized to track the (MPP) and maintain the operation of the system in it. MATLAB/Simulink is used to establish a model of photovoltaic system with (MPPT) function. This system is developed by combining the models established of solar PV module and DC-DC Boost converter. The system is simulated under different climate conditions. Simulation results show that the photovoltaic simulation system can track the maximum power point accurately.Keywords: Incremental conductance Algorithm, Perturb and Observe Algorithm, Photovoltaic System and Simulation Results.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 125912424 A Method for Quality Inspection of Motors by Detecting Abnormal Sound
Authors: Tadatsugu Kitamoto
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Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 170012423 A Control Model for the Dismantling of Industrial Plants
Authors: Florian Mach, Eric Hund, Malte Stonis
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The dismantling of disused industrial facilities such as nuclear power plants or refineries is an enormous challenge for the planning and control of the logistic processes. Existing control models do not meet the requirements for a proper dismantling of industrial plants. Therefore, the paper presents an approach for the control of dismantling and post-processing processes (e.g. decontamination) in plant decommissioning. In contrast to existing approaches, the dismantling sequence and depth are selected depending on the capacity utilization of required post-processing processes by also considering individual characteristics of respective dismantling tasks (e.g. decontamination success rate, uncertainties regarding the process times). The results can be used in the dismantling of industrial plants (e.g. nuclear power plants) to reduce dismantling time and costs by avoiding bottlenecks such as capacity constraints.
Keywords: Dismantling management, logistics planning and control models, nuclear power plant dismantling, reverse logistics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 145212422 Optimal Transmission Network Usage and Loss Allocation Using Matrices Methodology and Cooperative Game Theory
Authors: Baseem Khan, Ganga Agnihotri
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Restructuring of Electricity supply industry introduced many issues such as transmission pricing, transmission loss allocation and congestion management. Many methodologies and algorithms were proposed for addressing these issues. In this paper a power flow tracing based method is proposed which involves Matrices methodology for the transmission usage and loss allocation for generators and demands. This method provides loss allocation in a direct way because all the computation is previously done for usage allocation. The proposed method is simple and easy to implement in a large power system. Further it is less computational because it requires matrix inversion only a single time. After usage and loss allocation cooperative game theory is applied to results for finding efficient economic signals. Nucleolus and Shapely value approach is used for optimal allocation of results. Results are shown for the IEEE 6 bus system and IEEE 14 bus system.
Keywords: Modified Kirchhoff Matrix, Power flow tracing, Transmission Pricing, Transmission Loss Allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 259412421 Network Reconfiguration for Load Balancing in Distribution System with Distributed Generation and Capacitor Placement
Authors: T. Lantharthong, N. Rugthaicharoencheep
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This paper presents an efficient algorithm for optimization of radial distribution systems by a network reconfiguration to balance feeder loads and eliminate overload conditions. The system load-balancing index is used to determine the loading conditions of the system and maximum system loading capacity. The index value has to be minimum in the optimal network reconfiguration of load balancing. A method based on Tabu search algorithm, The Tabu search algorithm is employed to search for the optimal network reconfiguration. The basic idea behind the search is a move from a current solution to its neighborhood by effectively utilizing a memory to provide an efficient search for optimality. It presents low computational effort and is able to find good quality configurations. Simulation results for a radial 69-bus system with distributed generations and capacitors placement. The study results show that the optimal on/off patterns of the switches can be identified to give the best network reconfiguration involving balancing of feeder loads while respecting all the constraints.Keywords: Network reconfiguration, Distributed generation Capacitor placement, Load balancing, Optimization technique
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 422012420 Using Historical Data for Stock Prediction of a Tech Company
Authors: Sofia Stoica
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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices over the past five years of 10 major tech companies: Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We implemented and tested three models – a linear regressor model, a k-nearest neighbor model (KNN), and a sequential neural network – and two algorithms – Multiplicative Weight Update and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.
Keywords: Finance, machine learning, opening price, stock market.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 67512419 Power Flow Tracing Based Reactive Power Ancillary Service (AS) in Restructured Power Market
Authors: M. Susithra, R. Gnanadass
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Ancillary services are support services which are essential for humanizing and enhancing the reliability and security of the electric power system. Reactive power ancillary service is one of the important ancillary services in a restructured electricity market which determines the cost of supplying ancillary services and finding of how this cost would change with respect to operating decisions. This paper presents a new formation that can be used to minimize the Independent System Operator (ISO)’s total payment for reactive power ancillary service. The modified power flow tracing algorithm estimates the availability of reserve reactive power for ancillary service. In order to find optimum reactive power dispatch, Biogeography based optimization method (BPO) is proposed. Market Reactive Clearing Price (MRCP) is then estimated and it encourages generator companies (GENCOs) to participate in an ancillary service. Finally, optimal weighting factor and real time utilization factor of reactive power give the minimum ISO’s total payment. The effectiveness of proposed design is verified using IEEE 30 bus system.
Keywords: Biogeography based optimization method, Power flow tracing method, Reactive generation capability curve and Reactive power ancillary service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 323512418 An Improved Learning Algorithm based on the Conjugate Gradient Method for Back Propagation Neural Networks
Authors: N. M. Nawi, M. R. Ransing, R. S. Ransing
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The conjugate gradient optimization algorithm usually used for nonlinear least squares is presented and is combined with the modified back propagation algorithm yielding a new fast training multilayer perceptron (MLP) algorithm (CGFR/AG). The approaches presented in the paper consist of three steps: (1) Modification on standard back propagation algorithm by introducing gain variation term of the activation function, (2) Calculating the gradient descent on error with respect to the weights and gains values and (3) the determination of the new search direction by exploiting the information calculated by gradient descent in step (2) as well as the previous search direction. The proposed method improved the training efficiency of back propagation algorithm by adaptively modifying the initial search direction. Performance of the proposed method is demonstrated by comparing to the conjugate gradient algorithm from neural network toolbox for the chosen benchmark. The results show that the number of iterations required by the proposed method to converge is less than 20% of what is required by the standard conjugate gradient and neural network toolbox algorithm.Keywords: Back-propagation, activation function, conjugategradient, search direction, gain variation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 283812417 An Empirical Mode Decomposition Based Method for Action Potential Detection in Neural Raw Data
Authors: Sajjad Farashi, Mohammadjavad Abolhassani, Mostafa Taghavi Kani
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Information in the nervous system is coded as firing patterns of electrical signals called action potential or spike so an essential step in analysis of neural mechanism is detection of action potentials embedded in the neural data. There are several methods proposed in the literature for such a purpose. In this paper a novel method based on empirical mode decomposition (EMD) has been developed. EMD is a decomposition method that extracts oscillations with different frequency range in a waveform. The method is adaptive and no a-priori knowledge about data or parameter adjusting is needed in it. The results for simulated data indicate that proposed method is comparable with wavelet based methods for spike detection. For neural signals with signal-to-noise ratio near 3 proposed methods is capable to detect more than 95% of action potentials accurately.
Keywords: EMD, neural data processing, spike detection, wavelet decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 237512416 An Accurate, Wide Dynamic Range Current Mirror Structure
Authors: Hassan Faraji Baghtash
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In this paper, a low voltage high performance current mirror is presented. Its most important specifications, which are improved in this work, are analyzed and formulated proving that it has such outstanding merits as: Very low input resistance of 26mΩ, very wide current dynamic range of 8 decades from 10pA to 1mA (160dB) together with an extremely low current copy error of less than 0.6ppm, and very low input and output voltages. Furthermore, the proposed current mirror bandwidth is 944MHz utilizing very low power consumption (267μW) and transistors count. HSPICE simulation results are performed using TSMC 0.18μm CMOS technology utilizing 1.8V single power supply, confirming the theoretically proved outstanding performance of the proposed current mirror. Monte Carlo simulation of its most important parameter is also examined showing its sufficiently resistance against technology process variations.
Keywords: Current mirror/source, high accuracy, low voltage, wide dynamic range.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 223012415 Optimal Control Strategy for High Performance EV Interior Permanent Magnet Synchronous Motor
Authors: Mehdi Karbalaye Zadeh, Ehsan M. Siavashi
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The controllable electrical loss which consists of the copper loss and iron loss can be minimized by the optimal control of the armature current vector. The control algorithm of current vector minimizing the electrical loss is proposed and the optimal current vector can be decided according to the operating speed and the load conditions. The proposed control algorithm is applied to the experimental PM motor drive system and this paper presents a modern approach of speed control for permanent magnet synchronous motor (PMSM) applied for Electric Vehicle using a nonlinear control. The regulation algorithms are based on the feedback linearization technique. The direct component of the current is controlled to be zero which insures the maximum torque operation. The near unity power factor operation is also achieved. More over, among EV-s motor electric propulsion features, the energy efficiency is a basic characteristic that is influenced by vehicle dynamics and system architecture. For this reason, the EV dynamics are taken into account.Keywords: PMSM, Electric Vehicle, Optimal control, Traction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 176812414 Comparison of Two Interval Models for Interval-Valued Differential Evolution
Authors: Hidehiko Okada
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The author previously proposed an extension of differential evolution. The proposed method extends the processes of DE to handle interval numbers as genotype values so that DE can be applied to interval-valued optimization problems. The interval DE can employ either of two interval models, the lower and upper model or the center and width model, for specifying genotype values. Ability of the interval DE in searching for solutions may depend on the model. In this paper, the author compares the two models to investigate which model contributes better for the interval DE to find better solutions. Application of the interval DE is evolutionary training of interval-valued neural networks. A result of preliminary study indicates that the CW model is better than the LU model: the interval DE with the CW model could evolve better neural networks.
Keywords: Evolutionary algorithms, differential evolution, neural network, neuroevolution, interval arithmetic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 166712413 Subthreshold Circuit Performance Investigation under Temperature Variations
Authors: Mohd. Hasan, Ajmal Kafeel, S. D. Pable
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Ultra-low-power (ULP) circuits have received widespread attention due to the rapid growth of biomedical applications and Battery-less Electronics. Subthreshold region of transistor operation is used in ULP circuits. Major research challenge in the subthreshold operating region is to extract the ULP benefits with minimal degradation in speed and robustness. Process, Voltage and Temperature (PVT) variations significantly affect the performance of subthreshold circuits. Designed performance parameters of ULP circuits may vary largely due to temperature variations. Hence, this paper investigates the effect of temperature variation on device and circuit performance parameters at different biasing voltages in the subthreshold region. Simulation results clearly demonstrate that in deep subthreshold and near threshold voltage regions, performance parameters are significantly affected whereas in moderate subthreshold region, subthreshold circuits are more immune to temperature variations. This establishes that moderate subthreshold region is ideal for temperature immune circuits.Keywords: Subthreshold, temperature variations, ultralow power.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 230712412 Fast Complex Valued Time Delay Neural Networks
Authors: Hazem M. El-Bakry, Qiangfu Zhao
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Here, a new idea to speed up the operation of complex valued time delay neural networks is presented. The whole data are collected together in a long vector and then tested as a one input pattern. The proposed fast complex valued time delay neural networks uses cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically that the number of computation steps required for the presented fast complex valued time delay neural networks is less than that needed by classical time delay neural networks. Simulation results using MATLAB confirm the theoretical computations.Keywords: Fast Complex Valued Time Delay Neural Networks, Cross Correlation, Frequency Domain
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 182512411 Estimating Saturated Hydraulic Conductivity from Soil Physical Properties using Neural Networks Model
Authors: B. Ghanbarian-Alavijeh, A.M. Liaghat, S. Sohrabi
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Saturated hydraulic conductivity is one of the soil hydraulic properties which is widely used in environmental studies especially subsurface ground water. Since, its direct measurement is time consuming and therefore costly, indirect methods such as pedotransfer functions have been developed based on multiple linear regression equations and neural networks model in order to estimate saturated hydraulic conductivity from readily available soil properties e.g. sand, silt, and clay contents, bulk density, and organic matter. The objective of this study was to develop neural networks (NNs) model to estimate saturated hydraulic conductivity from available parameters such as sand and clay contents, bulk density, van Genuchten retention model parameters (i.e. r θ , α , and n) as well as effective porosity. We used two methods to calculate effective porosity: : (1) eff s FC φ =θ -θ , and (2) inf φ =θ -θ eff s , in which s θ is saturated water content, FC θ is water content retained at -33 kPa matric potential, and inf θ is water content at the inflection point. Total of 311 soil samples from the UNSODA database was divided into three groups as 187 for the training, 62 for the validation (to avoid over training), and 62 for the test of NNs model. A commercial neural network toolbox of MATLAB software with a multi-layer perceptron model and back propagation algorithm were used for the training procedure. The statistical parameters such as correlation coefficient (R2), and mean square error (MSE) were also used to evaluate the developed NNs model. The best number of neurons in the middle layer of NNs model for methods (1) and (2) were calculated 44 and 6, respectively. The R2 and MSE values of the test phase were determined for method (1), 0.94 and 0.0016, and for method (2), 0.98 and 0.00065, respectively, which shows that method (2) estimates saturated hydraulic conductivity better than method (1).Keywords: Neural network, Saturated hydraulic conductivity, Soil physical properties.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 255712410 Attention Multiple Instance Learning for Cancer Tissue Classification in Digital Histopathology Images
Authors: Afaf Alharbi, Qianni Zhang
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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper presents a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network-based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation on an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.
Keywords: Attention Multiple Instance Learning, Multiple Instance Learning, transfer learning, histopathological slides, cancer tissue classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22612409 High Efficiency Class-F Power Amplifier Design
Authors: Abdalla Mohamed Eblabla
Abstract:
Due to the high increase in and demand for a wide assortment of applications that require low-cost, high-efficiency, and compact systems, RF power amplifiers are considered the most critical design blocks and power consuming components in wireless communication, TV transmission, radar, and RF heating. Therefore, much research has been carried out in order to improve the performance of power amplifiers. Classes-A, B, C, D, E and F are the main techniques for realizing power amplifiers.
An implementation of high efficiency class-F power amplifier with Gallium Nitride (GaN) High Electron Mobility Transistor (HEMT) was realized in this paper. The simulation and optimization of the class-F power amplifier circuit model was undertaken using Agilent’s Advanced Design system (ADS). The circuit was designed using lumped elements.
Keywords: Power Amplifier (PA), Gallium Nitride (GaN), Agilent’s Advanced Design system (ADS) and lumped elements.
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