Body Wise Time Integration of Multi Body Dynamic Systems

2015 ◽  
pp. 55-61
Author(s):  
Wolfgang Witteveen
Keyword(s):  
Dynamic Systems ◽  
Time Integration ◽  
Multi Body ◽  
Body Dynamic

The energetic structure of multi-body dynamic systems

1978 ◽  
Vol 306 (2) ◽  
pp. 165-181 ◽  
Author(s):  
Dean Karnopp
Keyword(s):  
Dynamic Systems ◽  
Multi Body ◽  
Body Dynamic

Modeling and Simulation of a Full Vehicle With Parametric and External Uncertainties

2005 ◽  
Author(s):  
Lin Li ◽  
Corina Sandu ◽  
Adrian Sandu
Keyword(s):  
Dynamic Systems ◽  
Dynamic Models ◽  
Computational Technique ◽  
Computational Tools ◽  
Actuator Dynamics ◽  
Full Vehicle ◽  
Stochastic Function ◽  
Tire Stiffness ◽  
Multi Body ◽  
Body Dynamic

This paper presents the mathematical development of and simulation results for a full vehicle model with parametric uncertainties operating over unprepared terrain. The vehicle is modeled as a rigid multi-body dynamic system, consisting of chassis and four suspension and tire subsystems. The vehicle parameters considered uncertain are the suspension damping and the tire stiffness. The terrain profile is also modeled as a stochastic function. The uncertainties are explicitly represented using polynomial chaos decompositions. The computational technique presented in this study is more efficient than the traditional Monte Carlo approach, in modeling nonlinear multi-body dynamic systems with uncertainties. The numerical results presented here are very promising. The general computational tools discussed in this paper can be applied directly to any area that involves multi-body dynamic models, e.g., robotics, autonomous mechanical systems, actuator dynamics, and automatic control of systems with uncertainties.

Floating Time Algorithm for Time Optimal Control of Multi-Body Dynamic Systems

2005 ◽  
Vol 219 (3) ◽  
pp. 225-236 ◽  
Author(s):  
G Nakhaie Jazar ◽  
A Naghshineh-Pour
Keyword(s):  
Optimal Control ◽  
Dynamic System ◽  
Dynamic Systems ◽  
Time Optimal Control ◽  
Coordinate Space ◽  
Algebraic Equations ◽  
Initial State ◽  
Time Optimal ◽  
Multi Body ◽  
Body Dynamic

Moving a dynamic system in minimum time from a given initial state to a desired final state on a prescribed path is one of the oldest and most enduring technological dreams of the scientific and industrial communities. In this research, the problem of bounded-input time optimal control for applied multi-body dynamic systems subject to a full nonlinear dynamical model is solved. To solve the problem, an innovative method, called the ‘floating-time’ method is introduced and utilized. Compared to traditional methods, the floating-time method is an applied method not based on variational calculus. It can be applied to the full nonlinear model of the dynamical system and can handle static and dynamic constraints defined by differential or algebraic equations. The problem of time optimal control is as follows. Find the control law of bounded inputs that drive a given multi-body dynamic system (such as the gripper of a manipulator) along a pre-specified trajectory (in either configuration space or generalized coordinate space) from a given initial position to a given final position, minimizing the time of the motion as a performance index. Using variable time increments, the equations of motion of the system will be reduced to a set of algebraic equations. Searching for a set of time increments (floating-times) that make the equations to exert the maximum available effort produces the minimum possible floating-times, and minimizes the total time of motion. The applicability of the method will be shown by using three examples: a point mass sliding on a rough surface, a 2R robotic manipulator, and the well-known Brachistochrone.

scholarly journals Automated Linearization of Nonlinear Coupled Differential and Algebraic Equations

1991 ◽  
Author(s):  
Martin J. Vanderploeg ◽  
Jeff D. Trom
Keyword(s):  
Finite Difference ◽  
Dynamic Systems ◽  
Large Scale ◽  
Algebraic Equations ◽  
New Approach ◽  
Large Scale Systems ◽  
Equation Formulation ◽  
Equilibrium Configurations ◽  
Multi Body ◽  
Body Dynamic

Abstract This paper presents a new approach for linearization of large multi-body dynamic systems. The approach uses an analytical differentiation of terms evaluated in a numerical equation formulation. This technique is more efficient than finite difference and eliminates the need to determine finite difference pertubation values. Because the method is based on a relative coordinate formalism, linearizations can be obtained for equilibrium configurations with non-zero Cartesian accelerations. Examples illustrate the accuracy and efficiency of the algorithm, and its ability to compute linearizations for large-scale systems that were previously impossible.

The Multi-Body Dynamic Systems Cloud Computing and Simulation Based on Modelica

2012 ◽  
Vol 459 ◽  
pp. 454-457
Author(s):  
Yao Hui Li ◽  
Yong Qiang Dong ◽  
Yi Zhong Wu ◽  
Shu Ting Wang
Keyword(s):  
Cloud Computing ◽  
Dynamic Systems ◽  
Simulation Based ◽  
Multi Body ◽  
Body Dynamic

Rapid maneuvering of multi-body dynamic systems with optimal motion compensation

2015 ◽  
Vol 117 ◽  
pp. 209-221 ◽  
Author(s):  
B. Bishop ◽  
R. Gargano ◽  
A. Sears ◽  
M. Karpenko
Keyword(s):  
Dynamic Systems ◽  
Motion Compensation ◽  
Optimal Motion ◽  
Multi Body ◽  
Body Dynamic

A path following method for identifying static equilibrium in multi-body-dynamic systems

2018 ◽  
Vol 45 (3) ◽  
pp. 315-359
Author(s):  
Geoffrey K. Rose ◽  
Brett A. Newman ◽  
Duc T. Nguyen
Keyword(s):  
Dynamic Systems ◽  
Path Following ◽  
Static Equilibrium ◽  
Multi Body ◽  
Body Dynamic

Continuous multi-body dynamic analysis of float-over deck installation with rapid load transfer technique in open waters

2021 ◽  
Vol 224 ◽  
pp. 108729
Author(s):  
Shujie Zhao ◽  
Xun Meng ◽  
Huajun Li ◽  
Dejiang Li ◽  
Qiang Fu
Keyword(s):  
Dynamic Analysis ◽  
Load Transfer ◽  
Multi Body ◽  
Body Dynamic
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