scholarly journals An Optimal Estimation Method for Nonlinear Models of Mechanical Systems

1994 ◽  
Vol 116 (4) ◽  
pp. 805-810 ◽  
Author(s):  
M. J. G. van de Molengraft ◽  
F. E. Veldpaus ◽  
J. J. Kok
Keyword(s):  
Nonlinear Models ◽  
A Priori ◽  
Mechanical Systems ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Model Structure ◽  
Unknown Parameters ◽  
Starting Point ◽  
Nonlinear Mechanical ◽  
Nonlinear Mechanical Systems

This paper presents an optimal estimation method for nonlinear mechanical systems. The a priori knowledge of the system in the form of a nonlinear model structure is taken as a starting point. The method determines estimates of the parameters and estimates of the positions, velocities, accelerations, and inputs of the system. The optimal estimation method is applied to an experimental mechanical system. The unknown parameters in this system relate to inertia, friction and elastic deformation. It is shown that the optimal estimation method on the basis of a relatively simple model structure can lead to a useful description of the system.

scholarly journals Application of physical function model to state estimations of nonlinear mechanical systems

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Heisei Yonezawa ◽  
Itsuro Kajiwara ◽  
Shota Sato ◽  
Chiaki Nishidome ◽  
Takashi Hatano ◽  
...  
Keyword(s):  
Physical Function ◽  
Mechanical Systems ◽  
Function Model ◽  
Nonlinear Mechanical ◽  
State Estimations ◽  
Nonlinear Mechanical Systems

A Modified Algorithm for the Least Squares Identification

1983 ◽  
Vol 105 (1) ◽  
pp. 50-52
Author(s):  
C. Batur
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Mechanical Systems ◽  
Model Structure ◽  
Input Output ◽  
Unknown Parameters ◽  
Estimation Errors ◽  
Usual Practice ◽  
Unknown Disturbances ◽  
Modified Algorithm

To identify the dynamics of mechanical systems, the usual practice is to assume a certain model structure and try to estimate the unknown parameters of this model on the basis of input output observations. For mechanical systems operating under noisy industrial conditions, the number of unknowns of the problem exceeds the number of equations available. It is then inevitable that certain assumptions must be made on the unknown disturbances. This paper assumes that the only reliable feature of the disturbance is its independence of input. This yields a set of assumptions in excess of the minimal requirements and an endeavor has been made to exploit this excess to minimize the parameter estimation errors. Th resulting algorithm is similar to that of the Two Stage Least Squares method [1].

scholarly journals On the simulation technique of stochastic processes and nonlinear vibrations

1994 ◽  
Vol 16 (3) ◽  
pp. 23-31
Author(s):  
Nguyen Cao Menh ◽  
Tran Duong Tri
Keyword(s):  
Stochastic Processes ◽  
Nonlinear Vibrations ◽  
Mechanical Systems ◽  
Simulation Technique ◽  
Nonlinear Mechanical ◽  
Nonlinear Mechanical Systems

In this paper the procedure and program for simulation of stochastic processes are represented. The program is applied to nonlinear mechanical systems subjected to stochastic stationary excitation. The results obtained are compared with the ones from other methods which are used for estimating the exactitude of simulation technique.

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