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检索条件"主题词=Kalman Filter algorithm"

共 96 条记录，以下是61-70 订阅

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A New Method of Fault Phase Identification for High Voltage Transmission Lines Based on the Fault Component of Phase Voltage

A New Method of Fault Phase Identification for High Voltage ...

引用

2nd International Conference on Energy and Environmental Protection (ICEEP 2013)

作者： Chen Yang Hu Yan Tai Neng-ling Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai 200240 Peoples R China

ISBN: (纸本)9783037857434

Since the existing fault phase identification methods can not identify all fault types quickly and accurately for high voltage transmission lines, this article proposed a new method of fault phase identification based on the fault component of phase voltage difference and the kalman filter algorithm. The method defined the fault component's ratio of one phase voltage to the difference of the other two phase voltages as a fault phase identification factor. By analyzing the characteristics of fault phase identification factors in each fault type, the fault phase can be identified. Simulation results show that using the kalman filter algorithm to extract fundamental component is faster and more accurate. Meanwhile, the method can identify fault phases within half a cycle and is scarcely influenced by fault resistances, fault locations and fault initial phase angles. It also has a high sensitivity when the fault is on the side of strong source.

关键词： high voltage transmission line fault phase identification fault component of phase voltage kalman filter algorithm fourier algorithm

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RELIABLE SOC ESTIMATION FOR BATTERY POWERED EMBEDDED SYSTEM

RELIABLE SOC ESTIMATION FOR BATTERY POWERED EMBEDDED SYSTEM

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International Conference on Information Communication and Embedded Systems (ICICES)

作者： Johnsema, B. Janakiraman, K. SASTRA Univ Embedded Syst Thanjavur India SASTRA Univ Campus Fac Shanmugha Polytech Coll Thanjavur India

ISBN: (纸本)9781479938346

Lifetime constraint is the smallest mischance that could spell disaster to the entire embedded network. At most real time embedded devices are supported by battery backup. Low Battery life feeble the efficiency of the device, this may lead to catastrophe in hard real time. Hence lifetime constraint is considered as the significant issue in embedded device. This paper describes the solution for efficient lifetime. Battery management system is modeled by microcontroller to monitor and protect the battery pack. For safe working of the battery state of charge, SOC must be estimated. To improve the accuracy of the SOC, kalman filter algorithm is implemented. Battery management microcontroller communicates with host microcontroller to update the battery backup and state of health of the battery system. By the information received, host microcontroller schedules the task accordingly such that no catastrophic occurs.

关键词： State Of Charge (SOC) Battery management Microcontroller kalman filter algorithm

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Multiple Object Tracking for Similar, Monotonic Targets 10

Multiple Object Tracking for Similar, Monotonic Targets

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10th Institute-of-Electrical-and-Electronics-Engineers International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)

作者： Qian, Yifei Shi, Hui Tian, Maojin Yang, Runhuai Duan, Yuping Anhui Med Univ Dept Biomed Engn Hefei Anhui Peoples R China Univ Sci & Technol China Hefei Natl Lab Phys Sci Microscale Hefei 230026 Anhui Peoples R China Univ Sci & Technol China Dept Phys Hefei 230026 Anhui Peoples R China

ISBN: (纸本)9781728190099

As a vital and extremely hot branch of computer vision, multiple object tracking is widely used in security monitoring and biological behavior research. At present, the majority of the multiple object tracking algorithms are composed of two stages: detection and data association. There is often mutual interference between targets in each frame, which causes great trouble to object detection and correlation. Especially for the microscopic particles, detection and tracking always is a tricky business because of its similar appearance and irregular movement. In this paper, a multiple object tracking algorithm based on two-step detection is proposed for microscopic non-fluorescent labeled object with simple structure, monotonous features, even no obvious features for learning. The specific operation is: first threshold segment each image in video to extract targets from the background, and perform morphological operations on the obtained graph to separate the slightly adhesion targets to avoid incorrect tracking, then estimate object states by kalman filter and use Hungarian algorithm for data association, definitively achieve the goal of multiple object tracking. Experiments show that our algorithm is better than the general method, meeting the tracking task of multiple non-fluorescent labeled particles commendably.

关键词： multiple object tracking similar object simple object kalman filter algorithm particles tracking

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kalman filtering algorithm for electric power quality analysis: Harmonics and voltage sags problems. 6

Kalman filtering algorithm for electric power quality analys...

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6th Large Engineering Systems Conference on Power Engineering (LESCOPE 03)

作者： Mostafa, MA Ain Shams Univ Elect Power & Machines Dept Cairo Egypt

ISBN: (纸本)0780378636

Power quality involves how close the voltage waveform is to being a perfect sinusoid with a constant frequency and amplitude. In this paper, we review the applications of linear kalman filtering algorithm on-line for electric power quality analysis. These applications include the measurement of harmonics and voltage sags. Mathematical models for each problem are developed to suite the filter and tested using simulated examples. Conclusions are drawn at the end of the text.

关键词： kalman filter algorithm electric power quality harmonics voltage sags system identification

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Precise and Stable Feedback for Haptic Device with Exact Dynamics and Optimal Estimation 43

Precise and Stable Feedback for Haptic Device with Exact Dyn...

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43rd Annual Conference of the IEEE-Industrial-Electronics-Society (IECON)

作者： Lin, Weiyang Wu, Baibo Ding, Runze Qian, Cheng Yu, Xinghu Tong, Mingsi Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin 150080 Heilongjiang Peoples R China

ISBN: (纸本)9781538611272

In this paper, we propose a force feedback scheme for Delta device to improve precision and stability in master slave teleoperation. A simple and exact dynamical equation is created with principle of virtual work, which is easy to calculate in real-time. After analysing three items deep in dynamical equation, a reasonable strategy is designed to identify the mass of Delta mechanism. The identified parameters and dynamical equation are verified correct in ADAMS and MATLAB softwares. Simultaneously, following previous work on haptic interface, a suitable kalman filter algorithm is proposed to attain smooth contact force in real-time based on the impedance of environment, and simplified due to the short period of a cycle. Finally, a whole master-slave system is set up with CHAI3D toolkit, which consists of Phantom Omni, Computer and Delta device. With a force sensor mounted on the end, the contact force is measured in practice and then filtered with proposed algorithm. The final result shows that the estimated curve followed measured data well and lied at the center of original curve.

关键词： Delta Haptic device Exact Dynamics Human Machine Teleoperation kalman filter algorithm

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The Application of EKF in Parameter Identification of State-space Model 8

The Application of EKF in Parameter Identification of State-...

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8th International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)

作者： Zhang, Jing Zhou, Zuo Huang, Xiaona Hexi Univ Sch Informat Technol & Commun Zhangye 734000 Peoples R China Hexi Univ Sch Phys & Electromech Engn Zhangye 734000 Peoples R China

ISBN: (纸本)9781538682463

State-space model is an efficient tool for describing multiple input multiple output system, but the parameters identification of state-space model is a complicated problem, because in many cases, the parameters and state variables are all unknown in the model. Aiming at the shortcomings of the traditional identification method, in this paper, combined the unknown parameters and state variables of the state space model into a new state variable, then the linear state space model equation can be transformed into a nonlinear equation, and extended kalman filtering(EKF) algorithm is used to estimate the new state variables. In this way, we can implement double estimates of the unknown parameters and state variables. Doing simulation and analysis with Matlab, the results show that the method can realize parameter identification and state estimation of state-space model effectively, which has higher precision and accuracy.

关键词： State-space model Parameter identification State variables kalman filter algorithm Extended kalman filtering algorithm

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Output Current Identification Based on the kalman filtering algorithm for Magnetic-Coupling Excitation System 1

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International Conference on Wireless Power Transfer (ICWPT)

作者： Huang, Dongxiao Lin, Xianhong Hong, Zequan Yu, Xinhong Wang, Fengxiang Chinese Acad Sci Hai Xi Inst Quanzhou Inst Equipment Mfg Natl Local Joint Engn Res Ctr Elect Drives & Powe Quanzhou 362000 Peoples R China Fuzhou Univ Fuzhou 350108 Peoples R China Fujian Univ Technol Fujian Key Lab Intelligent Machining Technol & Eq Fuzhou 350118 Peoples R China

ISBN: (数字)9789819708734

ISBN: (纸本)9789819708758;9789819708734;9789819708727

Magnetic-coupling excitation system is one of the research highlights in the field of brushless Electrically Excited Synchronous Motor (EESM), which contains the primary energy emission device and a secondary receiving device that rotates synchronously with the motor rotor. Primary-side control estimation is widely applied in Wireless Power Transmission (WPT) system to detect the output current of the secondary device to reduce the weight of rotor and achieve the merit of communication-free. A magnetizing current estimation method based on the kalman filter algorithm is proposed for a novel system combined with EESM and WPT. The proposed method adopts the kalman filter algorithm to the magnetizing current estimation model, which eliminates the higher-order harmonics in the sampling of inverter current and transmitting coil current. In addition, the output current control is achieved by applying the PI controller. The simulation result of proposed system in Matlab/Simulink proves the enhancement of proposed method on the accuracy, the transient response speed and the tracking performance of magnetizing current estimation.

关键词： Wireless Power Transmission Electrically Excited Synchronous Motor Magnetizing Current Estimation kalman filter algorithm

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algorithm and Achieve of Self-balancing Two-wheeled Control System Based on PID Neural Network 6

Algorithm and Achieve of Self-balancing Two-wheeled Control ...

引用

6th International Conference on Electronics and Information Engineering (ICEIE)

作者： Zhao, Yan Wang, Jiang Hua Wang, Qi Yanching Inst Technol Yanjiao 065201 Peoples R China North China Inst Sci & Technol Yanjiao 065201 Peoples R China

ISBN: (纸本)9781510600294

For self-balancing two-wheeled vehicle position and angle control implementation issues, propose a control algorithm of self-balanced two-wheeled vehicle based on PID neural network. The algorithm overcomes the problem of PID controller generalization is weak, and can avoid over fitting and the BP neural network controller into a local optimum. The algorithm of the controller is constituted by a three-tier network, the first floor is the input layer, which receives two-wheel self-balancing vehicle position and Angle feedback information;a second layer of PID neuron layer, which is connected to the input layer, the state transition function respectively proportional function, integral function and the differential function;the third layer is the output layer, by weight in various proportions hidden layer output, the final composition of the control output of the controller. Control system fusion using kalman filter algorithm to get the self-balanced vehicle's attitude information. Through self-balancing two-wheeled vehicle actual experimental platform to verify the effectiveness of the control algorithm implementation.

关键词： self-balancing two-wheeled PID neural network kalman filter algorithm

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algorithm for Estimating SOC of Lithium-Ion Batteries Used for Electric Vehicles 12

Algorithm for Estimating SOC of Lithium-Ion Batteries Used f...

引用

12th International Symposium on Advanced Topics in Electrical Engineering (ATEE)

作者： Livint, Gheorghe Rusu, Florin A. Pintilie, Cosmin G. Gheorghe Asachi Tech Univ Iasi Fac Elect Engn & Appl Informat Iasi Romania

ISBN: (纸本)9781665418782

Energy storage systems represents a critical role in power supply of electric vehicles (EV) and lithium-ion batteries is the most promising and dominant energy storage choice. Because of cell variations in a battery pack it is hard to obtain an accurate model to study the behavior of lithium-ion cells and in many situations different algorithms must be used to estimate state of charge. Several techniques for SOC estimation have been studied in the last years. These methods can be classified in three categories: direct methods, data-driven methods and state-observation methods. In this paper it is the intention to estimate state-of-charge (SOC) of lithium-ion battery using a state-observation method such as kalman filter. The algorithm it is applied on an equivalent circuit model of a lithium-ion cell and after that can be extended to a pack of cells. Most of the time the performances are dependent on the measuring accuracy of current and open-loop calculation can lead to accumulated calculation errors due to uncertain disturbances from the practice application and lack of necessary corrective resolution. There are also other methods for estimating the SoC, like artificial neural networks, fuzzy logic, extended kalman filtering based estimators but the main disadvantage of these methods is represented by the differences between each individual cell which are ignored most of the time. In this case for reliable and accurate results should take in consideration individual cell's state, make calculation and the lowest SoC should be the reference point.

关键词： state of charge kalman filter algorithm battery model SOC optimization electric vehicles

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Design and Implementation of a Smart Belt for the Elderly 3

Design and Implementation of a Smart Belt for the Elderly

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3rd International Conference on Robotics, Artificial Intelligence and Intelligent Control (RAIIC)

作者： Piao, Xinan Jiang, Wenmei Hu, Chunyi Cai, Dongxin Dongguan City Univ Sch Artificial Intelligence Dongguan Peoples R China

ISBN: (纸本)9798350352634;9798350352627

Against the backdrop of the intensifying aging population in China, the issue of preventing falls among the elderly has become increasingly prominent. Statistics indicate that falls are one of the main causes of accidental injuries and deaths among the elderly, with the risk of falling being directly proportional to the age of the elderly. Due to the large range of activities of the elderly, methods that require the deployment of detection equipment in fixed locations have significant limitations. Multi-sensor detection devices are not easily portable and can impact the daily activities of the elderly. Therefore, this study proposes a wearable smart belt system aimed at addressing the high risk of falls and the difficulty of emergency rescue for the elderly. The accuracy of the device has been verified through experiments, capable of accurately detecting falls and correctly triggering the alarm function when a fall occurs, with the alarm function operating normally.

关键词： kalman filter algorithm Fall Detection Internet of Things Wireless Communication GPS Positioning

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