Sensory adaptation as Kalman filtering: theory and illustration with contrast adaptation

2003 ◽  
Vol 14 (3) ◽  
pp. 465-482 ◽  
Author(s):  
Norberto M Grzywacz ◽  
Joaquín de Juan
Keyword(s):  
Kalman Filtering ◽  
Sensory Adaptation ◽  
Filtering Theory ◽  
Contrast Adaptation

scholarly journals Kalman Filtering Applied to Induction Motor State Estimation

2020 ◽  
Author(s):  
Yassine Zahraoui ◽  
Mohamed Akherraz
Keyword(s):  
Kalman Filter ◽  
State Estimation ◽  
Induction Motor ◽  
Kalman Filtering ◽  
Speed Estimation ◽  
Stochastic Algorithm ◽  
State Variables ◽  
Extended Kalman Filtering ◽  
Filtering Theory ◽  
State Observation

This chapter presents a full definition and explanation of Kalman filtering theory, precisely the filter stochastic algorithm. After the definition, a concrete example of application is explained. The simulated example concerns an extended Kalman filter applied to machine state and speed estimation. A full observation of an induction motor state variables and mechanical speed will be presented and discussed in details. A comparison between extended Kalman filtering and adaptive Luenberger state observation will be highlighted and discussed in detail with many figures. In conclusion, the chapter is ended by listing the Kalman filtering main advantages and recent advances in the scientific literature.

Satellite Navigation System Positioning Research Based on Pseudo Linear Kalman Filtering Algorithm

2014 ◽  
Vol 687-691 ◽  
pp. 3996-3999
Author(s):  
Qi Lai Huang ◽  
Wei Bo Li ◽  
Zheng Gong ◽  
Han Li Wang
Keyword(s):  
Kalman Filtering ◽  
Satellite Navigation ◽  
National Defense ◽  
Filtering Theory ◽  
Satellite Navigation System ◽  
Filtering Algorithm ◽  
Performance Requirements ◽  
Positioning Method ◽  
Important Significance ◽  
Application Scope

At present, with application scope enlargement of GPS, traditional positioning method can't meet the growing performance requirements more and more. So kalman filtering theory is applied to national defense and civil enterprise in satellite navigation and it has very important significance.

Experimental Evaluation of the Preview Servo Scheme for a Two-Axis Positioning System

1984 ◽  
Vol 106 (1) ◽  
pp. 1-5 ◽  
Author(s):  
M. Tomizuka ◽  
D. Dornfeld ◽  
X.-Q. Bian ◽  
H.-G. Cai
Keyword(s):  
Kalman Filter ◽  
Kalman Filtering ◽  
Experimental Evaluation ◽  
Experimental Results ◽  
Positioning System ◽  
Velocity Control ◽  
Filtering Theory ◽  
On Line ◽  
Sharp Corners ◽  
Welding System

A preview servo scheme for position and velocity control is implemented on a two-axis welding table. The Kalman filtering theory is used to estimate the velocity from position measurements, and a cornering scheme is proposed to attain smaller path errors at sharp corners. The experimental results show that the preview-servo scheme with the Kalman filter and corner preview features is suitable for on-line control of the welding system.

Study of Back Analysis of Material Parameters of Mass Concrete

2011 ◽  
Vol 52-54 ◽  
pp. 768-772
Author(s):  
Wen Gai Lan ◽  
Xin Ming Zhao
Keyword(s):  
Kalman Filtering ◽  
Back Analysis ◽  
Mass Concrete ◽  
Mechanical Parameters ◽  
Coupling Problem ◽  
Filtering Theory ◽  
Filtering Method ◽  
Material Parameters ◽  
Research Fields ◽  
First Time

The Kalman filtering theory was applied for the back analysis of mechanical parameters of mass concrete on the first time. The time-spreading equation and the observation-correcting equation were deduced. After the coupling problem of extending Kalman filtering theory and FEM was solved, the Kalman-FEM formula were deduced and the corresponding back analysis procedures were given. The results indicate that the Kalman filtering method has good characteristics of convergence and stability. The broached method can be used in other research fields such as the back analysis of creeping parameters. Many more conclusions are tested and discussed through a classic example.

Fixed-Interval Kalman Smoother for Non-Square Descriptor Systems with Correlated Noise

2012 ◽  
Vol 433-440 ◽  
pp. 3601-3607
Author(s):  
Hang Wei Tian ◽  
Ying Shi
Keyword(s):  
State Estimation ◽  
Discrete Time ◽  
Kalman Filtering ◽  
Stochastic Systems ◽  
Fixed Interval ◽  
Descriptor Systems ◽  
Correlated Noise ◽  
Filtering Theory ◽  
Numerical Examples ◽  
Kalman Smoother

Based on the classical Kalman filtering theory, the state estimation problem is considered for non-square descriptor discrete time stochastic systems. Under Assumptions 1~3, a fixed-Interval Kalman smoother for non-square descriptor systems with correlated noise is given. Some numerical examples illustrate the effectiveness of the proposed algorithm.

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