New Weighted Adaptive Unscented Kalman Filter for Estimation of Hydraulic Systems

被引：0
|
作者：
Asl, Reza Mohammadi [1 ]
Handroos, Heikki [1 ]
机构：
[1] Lappeenranta Univ Technol, Lab Intelligent Machines, Lappeenranta, Finland
来源：
2018 GLOBAL FLUID POWER SOCIETY PHD SYMPOSIUM (GFPS) | 2018年
关键词：
Unscented Kalman filter; Hydraulic systems; State estimation; Time varying noise; STATE ESTIMATION; LINEAR-SYSTEMS; UNKNOWN INPUT; OBSERVER; DESIGN;
D O I：
暂无
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In this paper, a new weighted adaptive unscented Kalman filter is introduced. The proposed filter is trying to improve the performance of the previous versions. To have better results, it uses the previous estimation parameters to update itself. The proposed Kalman filter is applied to estimate the states of the nonlinear systems under time varying noise with time varying statistics. A hydraulic system, as a nonlinear system, is used as an application for the simulation. The results of the simulation are given.
引用
收藏
页数：6
相关论文
共 50 条
  • [1] A novel adaptive unscented Kalman filter for nonlinear estimation
    Jiang, Zhe
    Song, Qi
    He, Yuqing
    Han, Jianda
    PROCEEDINGS OF THE 46TH IEEE CONFERENCE ON DECISION AND CONTROL, VOLS 1-14, 2007, : 5805 - +
  • [2] State Estimation of Nonlinear Systems Using Novel Adaptive Unscented Kalman Filter
    Jargani, Lotfollah
    Shahbazian, Mehdi
    Salahshoor, Karim
    Fathabadi, Vahid
    ICET: 2009 INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES, PROCEEDINGS, 2009, : 124 - 129
  • [3] Optimized Exponential Square Root Unscented Kalman Filter for State Estimation of Hydraulic Systems
    Asl, Reza Mohammadi
    Mattila, Jouni
    2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC), 2022, : 76 - 81
  • [4] A New Robust Adaptive Fading Unscented Kalman Filter for Decentralized Dynamic State Estimation in Power Systems
    Chai, Bo
    Chan, S. C.
    2023 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, ISCAS, 2023,
  • [5] Adaptive Unscented Kalman Filter using Maximum Likelihood Estimation
    Mahmoudi, Zeinab
    Poulsen, Niels Kjolstad
    Madsen, Henrik
    Jorgensen, John Bagterp
    IFAC PAPERSONLINE, 2017, 50 (01): : 3859 - 3864
  • [6] Adaptive Unscented Kalman Filter for Estimation of Modelling Errors for Helicopter
    Song, Qi
    He, Yuqing
    2009 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO 2009), VOLS 1-4, 2009, : 2463 - +
  • [7] Adaptive unscented Kalman filter for neuronal state and parameter estimation
    Loïc J. Azzalini
    David Crompton
    Gabriele M. T. D’Eleuterio
    Frances Skinner
    Milad Lankarany
    Journal of Computational Neuroscience, 2023, 51 : 223 - 237
  • [8] Robust attitude estimation using an adaptive unscented Kalman filter
    Chiella, Antonio C. B.
    Teixeira, Bruno O. S.
    Pereira, Guilherme A. S.
    2019 INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2019, : 7748 - 7754
  • [9] Aerodynamic parameter estimation using adaptive unscented Kalman filter
    Majeed, M.
    Kar, Indra Narayan
    AIRCRAFT ENGINEERING AND AEROSPACE TECHNOLOGY, 2013, 85 (04): : 267 - 279
  • [10] Adaptive weighted measurement fusion unscented Kalman filter for multisensor system
    Hao G.
    Ye X.-F.
    Yuhang Xuebao/Journal of Astronautics, 2011, 32 (06): : 1400 - 1408
12345