A Discrete Suboptimal Adaptive Estimation Scheme for Linear Systems with Unknown Plant and Measurement Noise Covariances

1975 ◽  
Vol 8 (1) ◽  
pp. 471-477
Author(s):  
Claude A. Bozzo
Keyword(s):  
Linear Systems ◽  
Adaptive Estimation ◽  
Measurement Noise ◽  
Estimation Scheme

scholarly journals A Modified Extended Kalman Filter for a Two-Antenna GPS/INS Vehicular Navigation System

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3809 ◽  
Author(s):  
Yushi Hao ◽  
Aigong Xu ◽  
Xin Sui ◽  
Yulei Wang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Navigation System ◽  
Adaptive Estimation ◽  
Estimation Method ◽  
Measurement Noise ◽  
Model Errors ◽  
State Process ◽  
Stability And Accuracy ◽  
The Impact

Recently, the integration of an inertial navigation system (INS) and the Global Positioning System (GPS) with a two-antenna GPS receiver has been suggested to improve the stability and accuracy in harsh environments. As is well known, the statistics of state process noise and measurement noise are critical factors to avoid numerical problems and obtain stable and accurate estimates. In this paper, a modified extended Kalman filter (EKF) is proposed by properly adapting the statistics of state process and observation noises through the innovation-based adaptive estimation (IAE) method. The impact of innovation perturbation produced by measurement outliers is found to account for positive feedback and numerical issues. Measurement noise covariance is updated based on a remodification algorithm according to measurement reliability specifications. An experimental field test was performed to demonstrate the robustness of the proposed state estimation method against dynamic model errors and measurement outliers.

A treatment of nonwhite measurement noise in discrete linear systems

Automatica ◽  
1976 ◽  
Vol 12 (4) ◽  
pp. 371-374
Author(s):  
H.W. Brewer ◽  
C.T. Leondes
Keyword(s):  
Linear Systems ◽  
Measurement Noise ◽  
Discrete Linear Systems

scholarly journals An Adaptive Estimation Scheme for Open-Circuit Voltage of Power Lithium-Ion Battery

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Yun Zhang ◽  
Chenghui Zhang ◽  
Naxin Cui
Keyword(s):  
Lithium Ion Battery ◽  
Equivalent Circuit ◽  
Open Circuit Voltage ◽  
Adaptive Estimation ◽  
Equivalent Circuit Model ◽  
Lithium Ion ◽  
Open Circuit ◽  
Adaptive Scheme ◽  
Power Battery ◽  
Estimation Scheme

Open-circuit voltage (OCV) is one of the most important parameters in determining state of charge (SoC) of power battery. The direct measurement of it is costly and time consuming. This paper describes an adaptive scheme that can be used to derive OCV of the power battery. The scheme only uses the measurable input (terminal current) and the measurable output (terminal voltage) signals of the battery system and is simple enough to enable online implement. Firstly an equivalent circuit model is employed to describe the polarization characteristic and the dynamic behavior of the lithium-ion battery; the state-space representation of the electrical performance for the battery is obtained based on the equivalent circuit model. Then the implementation procedure of the adaptive scheme is given; also the asymptotic convergence of the observer error and the boundedness of all the parameter estimates are proven. Finally, experiments are carried out, and the effectiveness of the adaptive estimation scheme is validated by the experimental results.

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