An asymptotically more efficient non-linear state estimation scheme based on the stochastic approximation†

1977 ◽  
Vol 8 (9) ◽  
pp. 971-983 ◽  
Author(s):  
KATSUJI UOSAKI
Keyword(s):  
State Estimation ◽  
Stochastic Approximation ◽  
Non Linear ◽  
Estimation Scheme ◽  
Linear State

scholarly journals Reliable non-linear state estimation involving time uncertainties

Automatica ◽  
2018 ◽  
Vol 93 ◽  
pp. 379-388 ◽  
Author(s):  
Simon Rohou ◽  
Luc Jaulin ◽  
Lyudmila Mihaylova ◽  
Fabrice Le Bars ◽  
Sandor M. Veres
Keyword(s):  
State Estimation ◽  
Non Linear ◽  
Linear State

Adaptive central difference filter for non-linear state estimation

2015 ◽  
Vol 9 (6) ◽  
pp. 728-733 ◽  
Author(s):  
Manasi Das ◽  
Smita Sadhu ◽  
Tapan Kumar Ghoshal ◽  
Aritro Dey
Keyword(s):  
State Estimation ◽  
Central Difference ◽  
Non Linear ◽  
Difference Filter ◽  
Linear State

A non-linear multiple-model state estimation scheme for pipeline leak detection and isolation

2002 ◽  
Vol 216 (6) ◽  
pp. 497-512 ◽  
Author(s):  
H E Emara-Shabaik ◽  
Y A Khulief ◽  
I Hussaini
Keyword(s):  
Fluid Flow ◽  
State Estimation ◽  
Space Form ◽  
Multiple Model ◽  
Time Duration ◽  
Non Linear ◽  
Estimation Scheme ◽  
Short Time ◽  
Detection And Localization ◽  
Localization Of Leaks

Model-based monitoring schemes are known to have a great potential in detection and localization of leaks in pipelines. Fluid flow in pipelines is characterized by a system of non-linear-coupled partial differential equations. Since state estimation can provide the basis for real-time monitoring of fluid flow in pipelines, a suitable numerical scheme is employed to formulate the problem in state-space form, which enables the development of state estimation techniques. A modified extended Kalman filter (MEKF) in conjunction with feed forward computations to anticipate the leak magnitude provides the core of the adaptive multimodel state estimation technique used in this paper. Numerical simulation results show that the developed state estimation scheme effectively detects and locates small leaks in pipelines within a short time duration.

Non-Linear State estimation using pre-trained neural networks

2010 ◽  
Author(s):  
Enis Bayramoglu ◽  
Nils Axel Andersen ◽  
Ole Ravn ◽  
Niels Kjolstad Poulsen
Keyword(s):  
Neural Networks ◽  
State Estimation ◽  
Non Linear ◽  
Linear State
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