scholarly journals A Limit of the Recursive Least Square Method for the Parameter Estimation of Kalman Filter.

2000 ◽  
Vol 39 (1) ◽  
pp. 48-54
Author(s):  
Kaname SETO ◽  
Kohei ARAI
Keyword(s):  
Parameter Estimation ◽  
Kalman Filter ◽  
Least Square Method ◽  
Least Square ◽  
Recursive Least Square ◽  
Recursive Least Square Method

Inverse Active Load Inputs Estimation of the 3D Spatial Truss Structure System

2011 ◽  
Vol 27 (4) ◽  
pp. 469-477
Author(s):  
M.-H. Lee
Keyword(s):  
Finite Element ◽  
Kalman Filter ◽  
Least Square Method ◽  
Least Square ◽  
Truss Structure ◽  
Recursive Least Square ◽  
Finite Element Scheme ◽  
Element Scheme ◽  
Noise Covariance ◽  
Recursive Least Square Method

ABSTRACTThis study presents an innovative fuzzy inverse method with the finite-element scheme for estimating the unknown time-varying load inputs on a three-dimensional (3D) spatial truss structural system. The finite-element scheme is employed to discretize the problem in space, allowing multidimensional problems of various geometries to be treated. This method is based on the fuzzy Kalman Filter (FKF) technology and the fuzzy weighting recursive least square method (FWRLSM). The fuzzy Kalman filter measures the system responses at two distinct nodes in the 3D spatial truss structure. The fuzzy weighting recursive least square method is derived using the residual innovation sequence to compute the input loads. The proposed method's superiority is demonstrated using several typical simulation cases that vary with different estimator and the distinct levels of the initial process noise covariance and the measurement noise covariance. The results show that this method has great stability and accuracy.

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