Multibody Dynamics — Modeling and Analysis Methods

1991 ◽  
Vol 44 (3) ◽  
pp. 109-117 ◽  
Author(s):  
R. L. Huston
Keyword(s):  
Multibody Dynamics ◽  
Multibody Systems ◽  
System Modeling ◽  
Space Structures ◽  
Dynamics Modeling ◽  
Research Activity ◽  
Modeling And Analysis ◽  
Physical Systems ◽  
Systems Research ◽  
Recent Developments

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.

Dynamics Modeling and Analysis of a Reconfigurable Rotorcraft Unmanned Aerial Vehicle

ROBOT ◽  
2013 ◽  
Vol 35 (2) ◽  
pp. 227 ◽  
Author(s):  
Xiaogang RUAN ◽  
Xuyang HOU ◽  
Daoxiong GONG
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Dynamics Modeling ◽  
Modeling And Analysis ◽  
Aerial Vehicle

Multiple CMOS Intersection Measuring System Modeling and Analysis

2012 ◽  
Vol 614-615 ◽  
pp. 1299-1302
Author(s):  
Ming Jing Li ◽  
Yu Bing Dong ◽  
Guang Liang Cheng
Keyword(s):  
High Speed ◽  
High Performance ◽  
High Reliability ◽  
System Modeling ◽  
Position Effect ◽  
Field Of View ◽  
Measuring System ◽  
Price Ratio ◽  
Matlab Simulation ◽  
Modeling And Analysis

Multiple high speed CMOS cameras composing intersection system to splice large effect field of view(EFV). The key problem of system is how to locate multiple CMOS cameras in suitable position. Effect field of view was determined according to size, quantity and dispersion area of objects, so to determine camera position located on below, both sides and ahead to moving targets. This paper analyzes effect splicing field of view, operating range etc through establishing mathematical model and MATLAB simulation. Location method of system has advantage of flexibility splicing, convenient adjustment, high reliability and high performance-price ratio.

Recursive Linearization of Multibody Dynamics and Application to Control Design

1990 ◽  
Author(s):  
Tsung-Chieh Lin ◽  
K. Harold Yae
Keyword(s):  
Multibody Dynamics ◽  
Equations Of Motion ◽  
Linear Equations ◽  
Control Design ◽  
Numerical Differentiation ◽  
Difficult Problem ◽  
Computational Method ◽  
Computational Error ◽  
Dynamics Modeling ◽  
Analytical Approximations

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.

System modeling and analysis considerations

2019 ◽  
pp. 303-318
Author(s):  
Mark Aschheim ◽  
Enrique Hernández-Montes ◽  
Dimitrios Vamvatsikos
Keyword(s):  
System Modeling ◽  
Modeling And Analysis

scholarly journals Dynamic Response Optimization of Complex Multibody Systems in a Penalty Formulation Using Adjoint Sensitivity

2015 ◽  
Vol 10 (3) ◽  
Author(s):  
Yitao Zhu ◽  
Daniel Dopico ◽  
Corina Sandu ◽  
Adrian Sandu
Keyword(s):  
Sensitivity Analysis ◽  
Multibody Dynamics ◽  
Multibody Systems ◽  
Real Life ◽  
Design Parameters ◽  
Vehicle Model ◽  
Adjoint Sensitivity ◽  
Penalty Formulation ◽  
Sensitivity Approach ◽  
Dynamic Performance Analysis

Multibody dynamics simulations are currently widely accepted as valuable means for dynamic performance analysis of mechanical systems. The evolution of theoretical and computational aspects of the multibody dynamics discipline makes it conducive these days for other types of applications, in addition to pure simulations. One very important such application is design optimization for multibody systems. In this paper, we focus on gradient-based optimization in order to find local minima. Gradients are calculated efficiently via adjoint sensitivity analysis techniques. Current approaches have limitations in terms of efficiently performing sensitivity analysis for complex systems with respect to multiple design parameters. To improve the state of the art, the adjoint sensitivity approach of multibody systems in the context of the penalty formulation is developed in this study. The new theory developed is then demonstrated on one academic case study, a five-bar mechanism, and on one real-life system, a 14 degree of freedom (DOF) vehicle model. The five-bar mechanism is used to validate the sensitivity approach derived in this paper. The full vehicle model is used to demonstrate the capability of the new approach developed to perform sensitivity analysis and optimization for large and complex multibody systems with respect to multiple design parameters with high efficiency.

Dynamics Modeling of Elastic Multibody Systems Using Kane’s Method As Applied to a Flexible Robot

1997 ◽  
Author(s):  
Ali Meghdari ◽  
Farbod Fahimi
Keyword(s):  
Multibody Systems ◽  
Equations Of Motion ◽  
Component Mode Synthesis ◽  
Flexible Robot ◽  
Dynamics Modeling ◽  
Generalized Coordinates ◽  
Kane’S Method ◽  
Kane's Method ◽  
Elastic Multibody Systems ◽  
Elastic Form

Abstract Generalization of Kane’s equations of motion for elastic multibody systems is considered. Initially, finite element techniques are used to generate the elastic form of generalized coordinates. Then, the number of elastic coordinates are reduced by the component mode synthesis. Finally, Kane’s method is applied to obtain the equations of motion of such systems. Using this method, dynamic model of an elastic robot with one degree of freedom is presented.

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