Multibody Dynamics Modeling of Friction Winder Systems Using Absolute Nodal Coordination Formulation

Author(s):  
Liu Yi ◽  
Li Ji-Shun ◽  
Chen Guo-Ding ◽  
Xue Yu-Jun ◽  
Duan Ming-De
Author(s):  
Tsung-Chieh Lin ◽  
K. Harold Yae

Abstract The non-linear equations of motion in multi-body dynamics pose a difficult problem in linear control design. It is therefore desirable to have linearization capability in conjunction with a general-purpose multibody dynamics modeling technique. A new computational method for linearization is obtained by applying a series of first-order analytical approximations to the recursive kinematic relationships. The method has proved to be computationally more efficient. It has also turned out to be more accurate because the analytical perturbation requires matrix and vector operations by circumventing numerical differentiation and other associated numerical operations that may accumulate computational error.


2021 ◽  
pp. 94-102
Author(s):  
Mohamed Elshami ◽  
Mohamed Shehata ◽  
Qingshun Bai ◽  
Xuezeng Zhao

1991 ◽  
Vol 44 (3) ◽  
pp. 109-117 ◽  
Author(s):  
R. L. Huston

A review of recent developments in multibody dynamics modeling and analysis is presented. Multibody dynamics is one of the fastest growing fields of applied mechanics. Multibody systems are increasingly being employed as models of physical systems such as robots, mechanisms, chains, cables, space structures, and biodynamic systems. Research activity in multibody dynamics has stimulated research in a number of subfields including formulation methods, system modeling, numerical procedures, and graphical representations. These are also discussed and reviewed.


1994 ◽  
Vol 116 (2) ◽  
pp. 445-451 ◽  
Author(s):  
Tsung-Chieh Lin ◽  
K. Harold Yae

The nonlinear equations of motion in multibody dynamics pose a difficult problem in linear control design. It is therefore desirable to have linearization capability in conjunction with a general-purpose multibody dynamics modeling technique. A new computational method for linearization is obtained by applying a series of first-order analytical approximations to the recursive kinematic relationships. The method has proved to be computationally more efficient. It has also turned out to be more accurate because the analytical perturbation requires matrix and vector operations by circumventing numerical differentiation and other associated numerical operations that may accumulate computational error.


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