Estimation of model states for a hydraulic valve system using an extended Kalman filter

2017 ◽  
Author(s):  
◽  
Ahmed Al-Naseri
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Valve System ◽  
Hydraulic Valve

Application of Extended Kalman Filter in a Forced-Feedback Metering Poppet Valve System

2008 ◽  
Author(s):  
Chang Li ◽  
Roger Fales
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Linear Time ◽  
Control Volume ◽  
Load Pressure ◽  
Valve System ◽  
Poppet Valve ◽  
Parameter Variations ◽  
Measurement Noises ◽  
Optimal State Estimation

This work focuses on an accurate Extended Kalman Filter (EKF) estimator, which is applied in a forced-feedback metering poppet valve system (FFMPVS). The EKF estimator is used to estimate the position and velocity of the main poppet valve, the pilot poppet valve and the piston through using the control volume pressure, the load pressure and the pressure between the pilot poppet and the actuator housing, which are all disturbed by noise. The EKF estimator takes advantage of its recursive optimal state estimation to estimate the states of this metering poppet valve, which is a non-linear, time-variant dynamical system in real time. The EKF estimator has robustness to parameter variations and ability to filter measurement noises. It is shown that the EKF estimator tracks the states confidently and promptly for both the steady-state and transient performance, at the same time, the EKF estimator also filters the noise of the measured pressures.

scholarly journals Performance evaluation of GPS / BDS combined single-point positioning based on RTKLIB

2020 ◽  
Vol 165 ◽  
pp. 03009
Author(s):  
Li Yan-yi ◽  
Huang Jin ◽  
Tang Ming-xiu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Single Point ◽  
Least Square Method ◽  
Least Square ◽  
Filter Method ◽  
Single System ◽  
Positioning Error ◽  
Dual Mode ◽  
Kalman Filter Method

In order to evaluate the performance of GPS / BDS, RTKLIB, an open-source software of GNSS, is used in this paper. In this paper, the least square method, the weighted least square method and the extended Kalman filter method are respectively applied to BDS / GPS single system for data solution. Then, the BDS system and GPS system are used for fusion positioning and the positioning results of the two systems are compared with that of the single system. Through the comparison of experiments, on the premise of using the extended Kalman filter method for positioning, when the GPS signal is not good, BDS data is introduced for dual-mode positioning, the positioning error in e direction is reduced by 36.97%, the positioning error in U direction is reduced by 22.95%, and the spatial positioning error is reduced by 16.01%, which further reflects the advantages of dual-mode positioning in improving a system robustness and reducing the error.

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