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检索条件"主题词=Filtering algorithms"

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Model Predictive Control for High-Speed Flywheel Systems

Model Predictive Control for High-Speed Flywheel Systems

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Electrical Engineering and Control Science (IC2ECS), International Conference on

作者： Xiao Liu Congzhe Gao Haoying Fu Ziwei Wang School of Automation Beijing Institute of Technology Beijing China

ISBN: (数字)9798331510107

ISBN: (纸本)9798331510114

In high-speed flywheel systems, permanent magnet synchronous motors (PMSMs) are the preferred choice. However, the low inductance of PMSM and the lower ratio of carrier cause increased current harmonics, which means more motor losses. The LC filter is widely used to suppress current harmonics, but closed-loop current control may be affected by the filter. In this paper, a mathematical model of the system is established to implement the finite control set model predictive control (FCS-MPC) method. The conditions of active damping for the MPC method are obtained by the analysis of the resonance principle. It is shown that capacitor voltage control reduces total harmonic distortion of the motor stator current by the simulation result.

关键词： Damping Simulation Magnetic separation Software algorithms filtering algorithms Harmonic analysis Resonance Flywheels Power harmonic filters Predictive control

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Weighted Model-Based State-of-Charge Estimation Algorithm for Differential Terminal Voltage Application of LFP Battery

Weighted Model-Based State-of-Charge Estimation Algorithm fo...

引用

IEEE Energy Conversion Congress and Exposition, ECCE

作者： Minhyeok Kim Eunjin Kang Seongkyu Lee Minwoo Song Bomyeong Ko Jaea Lee Woonki Na Jonghoon Kim Department of Electrical Engineering Chungnam National University Daejeon Republic of Korea Department of Electrical and Computer Engineering California State University Fresno USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Accurate State-of-Charge (SOC) estimation of Lithium-Iron-Phosphate (LFP) batteries is crucial for Electric Vehicles (EVs) Battery Management System (BMS) as it reflects information about the cell internal state and lifespan, serving as a vital indicator for battery operation in BMS. However, precise SOC estimation for LFP batteries is challenging due to their hysteresis characteristics, which minimize voltage variations. Therefore, this paper applies the Extended Kalman Filter (EKF) to estimate SOC using terminal voltage derived from a weighted model combining Open Circuit Voltage (OCV) and Thevenin model. This method aims to enhance SOC estimation accuracy, address issues arising from LFP battery characteristics, and improve the overall performance of EV battery systems.

关键词： Accuracy Estimation Voltage filtering algorithms Electric vehicles Batteries State of charge Kalman filters Integrated circuit modeling Hysteresis

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Research on Robot Path Planning Algorithm for Filter Plate Cleaning of Plate and Frame Filter Press

Research on Robot Path Planning Algorithm for Filter Plate C...

引用

Artificial Intelligence and Intelligent Manufacturing (AIIM), International Symposium on

作者： Jie Xu Long Cui Yongguo Zhao Xincheng Tian Center for Robotics School of Control Science and Engineering Shandong University Jinan China Engineering Research Center of Intelligent Unmanned System Ministry of Education Jinan China Shandong Academy of Sciences Institute of Automation Qilu University of Technology Jinan China

ISBN: (数字)9798331541729

ISBN: (纸本)9798331541736

Plate and frame filter press is an important solid-liquid separation equipment that plays an important role in many fields. The filter plate is one of the core components of the frame filter press, and its main function is to support the filter cloth and form a filter chamber. After the filtration process of the filter press is completed, a large number of impurities are often attached to the filter plate, so it is of great value to study the impurity cleaning problem of the filter plate of the plate and frame filter press. In this paper, aiming at the cleaning process of the filter plate of the plate and frame filter press, the image information of the filter plate is obtained by visual means, and then the image is analyzed and processed to obtain the position information of the impurities of the filter plate, the path planning of the obtained position information is carried out, and finally the robot is made to complete the cleaning task efficiently and accurately according to the planned path, which has certain practical value.

关键词： Presses Visualization Impurities Image processing filtering algorithms Information filters Cleaning Path planning Manufacturing Robots

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Evaluating Data-Driven System Identification Methods for DC Microgrids in the Presence of Noise

Evaluating Data-Driven System Identification Methods for DC ...

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International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

作者： Leila Kamyabi Rasool Peykarporsan Tek Tjing Lie School of Engineering Auckland University of Technology Auckland New Zealand Dept. Electrical Engineering Auckland University of Technology Auckland New Zealand

ISBN: (数字)9798350372786

ISBN: (纸本)9798350372793

This paper explores the concept of system model identification through input-output data analysis. It focuses on three prominent mathematical approaches: Balanced Proper Orthogonal Decomposition (BPOD), Eigensystem Realization Algorithm (ERA), and Observer/Kalman Filter Identification (OKID). A six-state microgrid (MG) system serves as the test case, further exposed to noise during data collection to bridge the gap between simulation and real-world conditions. To assess the performance of each approach under noise, MATLAB simulations are employed. The results reveal that while BPOD exhibits the highest noise tolerance, its real-world applicability is limited due to implementation constraints. Conversely, OKID demonstrates a balance of robustness and accuracy, making it a more viable option for practical system model identification.

关键词： Accuracy Noise Microgrids filtering algorithms Rendering (computer graphics) Mathematical models Robustness

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Performance Improvement of DFT-s OFDM Systems Leveraging Non-Orthogonal Matrix Precoding

Performance Improvement of DFT-s OFDM Systems Leveraging Non...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Peiji Song Zhouyi Hu Li Pei Chun-kit Chan Department of Information Engineering The Chinese University of Hong Kong Hong Kong China Key Laboratory of All-Optical Networks and Modern Communication Networks of Ministry of Education Institute of Lightwave Technology Beijing Jiaotong University Beijing China

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

The non-orthogonal matrix precoding (NOM-p) is proposed to avoid signal-to-noise ratio dips in discrete-Fourier-transform spread (DFT-s) orthogonal frequency division multiplexing (OFDM) signals. Simulation results verify its performance superiority over the conventional DFT-s OFDM and the recently reported chirp-like polyphase sequence (CLPS) precoded scheme.

关键词： Optical filters OFDM Precoding Simulation Discrete Fourier transforms filtering algorithms Optical fiber communication Frequency division multiplexing Signal to noise ratio Photonics

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Comparative Study of Feature Selection algorithms for Text Analytics: A Performance and Efficiency Analysis

Comparative Study of Feature Selection Algorithms for Text A...

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Recent Advances in Science and Engineering Technology (ICRASET), International Conference on

作者： Emad Qais Mn Veena P.E.T Research Foundation University of Mysore Mandya Karnataka India Department of MCA P.E.S. College of Engineering Mandya Karnataka India

ISBN: (数字)9798350388602

ISBN: (纸本)9798350388619

In text analytics, high-dimensional datasets frequently impede model performance, rendering feature selection an essential process for enhancing accuracy and computing efficiency. This study examines and contrasts various feature selection algorithms, classified into filter, wrapper, and embedded techniques, within the realm of text analytics. The study evaluates the effectiveness of approaches including ChiSquared, Recursive Feature Elimination (RFE), and L1 Regularization on benchmark text datasets to ascertain their competence in dimensionality reduction while maintaining model performance. The findings illustrate the trade-offs between computational cost and performance, offering insights into the optimal use of feature selection techniques for various text classification tasks.

关键词： Analytical models Computational modeling Text categorization filtering algorithms Feature extraction Rendering (computer graphics) Computational efficiency Classification algorithms Random forests Genetic algorithms

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Adaptive Kalman Filter with Probabilistic Gain Adjustment for Estimation of Satellite Position in the Presence of Measurement Faults

Adaptive Kalman Filter with Probabilistic Gain Adjustment fo...

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International Scientific Conference Electronics (ET)

作者： C. Hajiyev T. Y. Erkec U. Hacizade D. Cilden-Guler Dept. of Aeronautical Engineering Istanbul Technical University Istanbul Turkey Turkish National Defence University Atatürk Strategic Studies and Graduate Inst Istanbul Turkiye Dept. of Computer Eng Halic University Istanbul Turkiye

ISBN: (数字)9798350376449

ISBN: (纸本)9798350376456

In this study, a probabilistic adaptive filtering technique is described for the Extended Kalman filter (EKF) algorithm, which is used to estimate Low Earth Orbit (LEO) satellite position, velocity, and clock bias using Global Navigation Satellite System (GNSS) distance measurements. The proposed probabilistic adaptive extended Kalman filter (pAEKF) algorithm is based on tracking normalized innovation sequences in the filter and calculating the probability of normal operation of the estimation system. The filter gain is adjusted based on this probability to maintain the filter’s tracking performance despite inaccurate measurements.

关键词： Satellites Adaptive systems Low earth orbit satellites Estimation filtering algorithms Gain measurement Position measurement Extraterrestrial measurements Probabilistic logic Kalman filters

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Comparative Analysis of DFT and Quadrature Demodulation algorithms for Complex Spectrum Measurements

Comparative Analysis of DFT and Quadrature Demodulation Algo...

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International Scientific Symposium on Metrology and Metrology Assurance (MMA)

作者： Sergey A. Podobuev Anna A. Krylovich Alexandra E. Evsenkina Alexander A. Shatokhin Nikolay A. Serov Andrey N. Serov Diagnostic Information Technologies Department National Research University “Moscow Power Engineering Institute” Moscow Russian Federation Computing Machines Systems and Networks Department National Research University “Moscow Power Engeneering Institute” Moscow Russian Federation

ISBN: (数字)9798350352832

ISBN: (纸本)9798350352849

To measure the signal spectrum, algorithms based on the implementation of the discrete Fourier transform and quadrature demodulation take place. All of the approaches under consideration are difficult to implement. In addition, the quadrature demodulation method has the potential to have significantly greater accuracy. The main reason for the occurrence of methodological measurement error in the case of DFT algorithms is the “spectrum leakage” effect. Estimating this error causes significant difficulties. The work shows that for the case of using a quadrature demodulator with an output filter of the moving average type, the discrete Fourier transform and the quadrature demodulator are mathematically equivalent. Simulation modeling of the most popular DFT implementation algorithms (direct implementation, Goertzel algorithm, DFT as filtering and fast Fourier transform) has been carried out. For the quadrature demodulation method, the influence of the output filter on the resulting error in measuring the amplitude and phase spectra of the signal is considered. The results of simulation and mathematical modeling were compared to confirm the reliability of the results.

关键词： Fast Fourier transforms Discrete Fourier transforms Measurement uncertainty filtering algorithms Length measurement Metrology Time measurement Mathematical models Frequency measurement Demodulation

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Anti-interference Pine Wilt Disease Detection Algorithm Based on Multilevel Residual Fusion in YOLOv8

Anti-interference Pine Wilt Disease Detection Algorithm Base...

引用

IEEE International Conference on Smart Internet of Things (SmartIoT)

作者： Lina Wang Junchao Yuan Jijing Cai Jiangtao Deng Zijia Yang Zhihao Wen Kai Fang Hailin Feng Zhejiang A&F University Hangzhou China Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9798350366440

ISBN: (纸本)9798350366457

Pine Wilt Disease (PWD) can severely threaten the health of pine trees. Monitoring pine forests with drones can effectively prevent the spread of PWD. Existing object detection models maintain high recognition accuracy under normal conditions, but their accuracy significantly decreases when there are conditions such as cloud cover and atmospheric scattering. Therefore, this paper proposes an anti-interference pine wilt disease detection algorithm based on multilevel residual fusion in YOLOv8, named YOLOv8-MD. We designed a Multi-level Residual module (MRes), which can filter out image noise. The MRes module not only effectively enhances the detail features of small targets in images but also filters out image noise through the structure of multi-level residual blocks. Additionally, we integrated a Dynamic Upsampling algorithm (DySample) into the Neck. DySample module improves the quality of feature maps during the upsampling process by adaptively adjusting the sampling points. We simulated the situation of cloud cover using Gaussian noise. Experimental results show that, at an interference ratio of 100% and an interference intensity of 7, the average precision of the YOLOv8-MD model improved by 6.5%, 8.2%, and 7.6% compared to three traditional object detection models.

关键词： Adaptation models Forests Heuristic algorithms Interference Object detection filtering algorithms Neck Monitoring Diseases Drones

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Improved Fast NLMS algorithm based on variable forgetting factor technique for acoustic echo cancellation

Improved Fast NLMS algorithm based on variable forgetting fa...

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International Conference on Image and Signal Processing and their Applications (ISPA)

作者： Mohamed Yacine Bensouda Ahmed Benallal LATSI Laboratory University of Blidal Blida Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

The recursive least squares (RLS) algorithm is widely used in various adaptive filtering applications, mostly due to its rapid convergence rate. The forgetting factor is a crucial parameter in this algorithm. For a fixed value for this parameter, there is a tradeoff between misalignment and tracking. Nevertheless, the use of a variable forgetting factor (VFF) approach gives a better compromise between the performance criteria of the RLS algorithm. Nonetheless, the algorithm's computational complexity presents a notable challenge, particularly in scenarios that involve lengthy adaptive filters, such as acoustic echo cancellation (AEC). This paper incorporates the concept of a variable forgetting factor into the fast normalized least mean squares (FNLMS) algorithm. The FNLMS algorithm demonstrates performances comparable to the RLS algorithm while maintaining a computational complexity similar to that of the normalized least mean squares (NLMS) algorithm. Based on simulation results in the context of AEC, the proposed VFF-FNLMS algorithm exhibits better performances in terms of convergence speed and tracking ability when compared to both FNLMS and NLMS algorithms.

关键词： Echo cancellers filtering Simulation Signal processing algorithms Adaptive filters Signal processing filtering algorithms

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