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FPGA Implementation of Extended Kalman Filter for Parameters estimation of Railway Wheelset

Computers, Materials & Continua 2023年第2期74卷 3351-3370页

作者： Khakoo Mal Tayab Din Memon Imtiaz Hussain Kalwar Bhawani Shankar Chowdhry Department of Electronic Engineering Mehran University of Engineering&TechnologyJamshoro76062Pakistan Sukkur IBA University Sukkur65200Pakistan Design and Creative Technology Torrens University Australia196 Flinders StreetMelbourne3000VICAustralia Department of Electronics and Power Engineering Pakistan Navy Engineering College NUSTKarachi75350Pakistan NCRA-Condition Monitoring Systems Lab Mehran University of Engineering&TechnologyJamshoro76062Pakistan

It is necessary to know the status of adhesion conditions between wheel and rail for efficient accelerating and decelerating of railroad *** proper estimation of adhesion conditions and their real-time implementation is considered a challenge for *** this paper,the development of simulation model of extended Kalman filter(EKF)in MATLAB/Simulink is presented to estimate various railway wheelset parameters in different contact conditions of *** to concurrent in nature,the Xilinx®System-on-Chip Zynq Field Programmable Gate Array(FPGA)device is chosen to check the onboard estimation ofwheel-rail interaction parameters by using the National Instruments(NI)myRIO®development *** NImyRIO®development board is flexible to deal with nonlinearities,uncertain changes,and fastchanging dynamics in real-time occurring in wheel-rail contact conditions during vehicle *** simulated dataset of the railway nonlinear wheelsetmodel is tested on FPGA-based EKF with different track conditions and with accelerating and decelerating operations of the *** proposed model-based estimation of railway wheelset parameters is synthesized on FPGA and its simulation is carried out for functional verification on *** obtained simulation results are aligned with the simulation results obtained through *** the best of our knowledge,this is the first time study that presents the implementation of a model-based estimation of railway wheelset parameters on FPGA and its functional *** functional behavior of the FPGA-based estimator shows that these results are the addition of current knowledge in the field of the railway.

关键词： Adhesion force extended kalman filter FPGA implementation railway wheelset real-time estimation wheel-rail interaction

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Diffusion LMS algorithm in wireless sensor networks with multiplicative input noise 36

Diffusion LMS algorithm in wireless sensor networks with mul...

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第36届中国控制会议

作者： Wei Huang Ying Li College of Computer Science and Technology Zhejiang University of Technology

ISBN: (纸本)9781538629185

In this paper,we propose the bias-compensated distributed diffusion LMS algorithm to estimate the parameter in the presence of multiplicative regressor noise to mitigate the estimation bias caused by multiplicative regressor *** the case where the multiplicative regressor noise exists,the estimate produced by standard distributed diffusion LMS algorithm will be *** validate the algorithm,we first assume that the variance of the regressor noise is a priori known,and then we use a real-time estimation method to estimate the variance and replace the hypothesis with the estimated ***,we show that our proposed algorithm can indeed mitigate the estimation bias,and can achieve better performance than the standard distributed diffusion algorithm through computer simulations.

关键词： diffusion least-mean square(dLMS) multiplicative regressor noise unbiased estimation real-time estimation

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Event-Trigger Extended Kalman Filter Design for Distributed Generation Network with Limited Communication 36

Event-Trigger Extended Kalman Filter Design for Distributed ...

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第36届中国控制会议

作者： Xing Xin Luyu Li Sen Li Zhen Li Jian Li Zhen Chen Xiangdong Liu Beijing Institute of Electronic System Engineering School of Automation & Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781538629185

For distributed generation（DG） network, it is important to estimate the real-time states. The information-centric networking（ICN） is established to take charge of the communication of DG network. However, the assumption of ideal communication between sensors and the estimation center cannot be guaranteed due to the communication constraints of ICN with the increasing DG network. A conventional algorithm, which reduces the communication burden in ICN, is to drop the observation of each smart grid in a random way. However, the accuracy of this algorithm recession decays rapidly with the increasing drop rate. To guarantee an appropriate estimation accuracy when the drop rate increases, this paper introduces the event-trigger strategy into the estimation algorithm. An event-trigger extended kalman filter（ET-EKF） is established in this paper to adapt the nonlinearity of DG system. ET-EKF reduces the communication burden and achieves an appropriate estimation accuracy at the same time. Finally, its feasibility and performance are demonstrated using the standard IEEE 39-bus system with phasor measurement units（PMUs）.

关键词： Event-trigger extended Kalman filter(ET-EKF) real-time estimation distributed generation network smart grids phasor measurement unit(PMU)

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