A Computational Method for Formulation and Solution of Dynamical Equations for Complex Mechanisms and Multibody Systems

2017 ◽  
Author(s):  
Kristopher Wehage ◽  
Bahram Ravani
Keyword(s):  
Multibody Systems ◽  
Sparse Matrix ◽  
Equations Of Motion ◽  
Schur Complement ◽  
Computational Method ◽  
Dynamical Equations ◽  
Multibody Dynamic ◽  
Sparse Matrix Techniques ◽  
Complex Mechanisms ◽  
Coordinate Partitioning

This paper presents a computational method for formulating and solving the dynamical equations of motion for complex mechanisms and multibody systems. The equations of motion are formulated in a preconditioned form using kinematic substructuring with a heuristic application of Generalized Coordinate Partitioning (GCP). This results in an optimal split of dependent and independent variables during run time. It also allows reliable handling of end-of-stroke conditions and bifurcations in mechanisms, thereby facilitating dynamic simulation of paradoxical linkages such as Bricard’s mechanism that has been known to cause problems with some multibody dynamic codes. The new Preconditioned Equations of Motion are then solved using a recursive formulation of the Schur Complement Method combined with Sparse Matrix Techniques. In this fashion the Preconditioned Equations of Motion are recursively uncoupled and solved one kinematic substructure at a time. The results are demonstrated using examples.

Dynamics of Constrained Multibody Systems

1984 ◽  
Vol 51 (4) ◽  
pp. 899-903 ◽  
Author(s):  
J. W. Kamman ◽  
R. L. Huston
Keyword(s):  
Multibody Systems ◽  
Equations Of Motion ◽  
Governing Equations ◽  
Dynamical Equations ◽  
Closed Loops ◽  
Constrained Multibody Systems ◽  
Constraint Equations ◽  
Cable Dynamics ◽  
Hanging Chain ◽  
A Chain

A new automated procedure for obtaining and solving the governing equations of motion of constrained multibody systems is presented. The procedure is applicable when the constraints are either (a) geometrical (for example, “closed-loops”) or (b) kinematical (for example, specified motion). The procedure is based on a “zero eigenvalues theorem,” which provides an “orthogonal complement” array which in turn is used to contract the dynamical equations. This contraction, together with the constraint equations, forms a consistent set of governing equations. An advantage of this formulation is that constraining forces are automatically eliminated from the analysis. The method is applied with Kane’s equations—an especially convenient set of dynamical equations for multibody systems. Examples of a constrained hanging chain and a chain whose end has a prescribed motion are presented. Applications in robotics, cable dynamics, and biomechanics are suggested.

A Novel Approach for Decoupling of Dynamical Equations of Flexible Manipulators

1999 ◽  
Author(s):  
Ali Meghdari ◽  
Farbod Fahimi
Keyword(s):  
Multibody Systems ◽  
Equations Of Motion ◽  
Flexible Manipulator ◽  
Flexible Manipulators ◽  
Dynamical Equations ◽  
First Order ◽  
Novel Approach ◽  
Elastic Multibody Systems ◽  
Two Degree Of Freedom ◽  
Generalized Coordinate

Abstract Recent advances in the study of dynamics of elastic multibody systems, specially the flexible manipulators, indicate the need and importance of decoupling the equations of motion. In this paper, an improved method for deriving elastic generalized coordinates is presented. In this regard, the Kane’s equations of motion for elastic multibody systems are considered. These equations are in the generalized form and may be applied to any desired holonomic system. Flexibility in choosing generalized speeds in terms of generalized coordinate derivatives in Kane’s method is used. It is shown that proper choice of a congruency transformation between generalized coordinate derivatives and generalized speeds leads to a series of first order decoupled equations of motion for holonomic elastic multibody systems. Furthermore, numerical implementation of the decoupling technique using congruency transformation is discussed and presented via simulation of a two degree of freedom flexible manipulator.

scholarly journals About the Gibbs-Appel equations for multibody systems

2006 ◽  
Vol 28 (4) ◽  
pp. 225-229
Author(s):  
Nguyen Van Khang
Keyword(s):  
Multibody Dynamics ◽  
Multibody Systems ◽  
Equations Of Motion ◽  
Automatic Generation ◽  
Matrix Form ◽  
Dynamical Equations

In this paper a matrix form of Gibbs-Appel function is recommended for multibody dynamics formulations. The form proposed in this paper seems to be more clear and suitable for automatic generation of dynamical equations of motion. The advantages followed from the formulation proposed are illustrated through an example.

Implicit Numerical Integration of Constrained Equations of Motion Via Generalized Coordinate Partitioning

1992 ◽  
Vol 114 (2) ◽  
pp. 296-304 ◽  
Author(s):  
E. J. Haug ◽  
Jeng Yen
Keyword(s):  
Numerical Integration ◽  
Equations Of Motion ◽  
Integration Algorithm ◽  
Differentiation Formula ◽  
Generalized Coordinates ◽  
Multibody Dynamic ◽  
Constrained Equations ◽  
Automated Simulation ◽  
Coordinate Partitioning ◽  
Generalized Coordinate

An implicit, stiffly stable numerical integration algorithm is developed and demonstrated for automated simulation of multibody dynamic systems. The concept of generalized coordinate partitioning is used to parameterize the constraint set with independent generalized coordinates. A stiffly stable, Backward Differentiation Formula (BDF) numerical integration algorithm is used to integrate independent generalized coordinates and velocities. Dependent generalized coordinates, velocities, and accelerations, as well as Lagrange multipliers that account for constraints, are explicitly retained in the formulation to satisfy all of the governing kinematic and dynamic equations. The algorithm is shown to be valid and accurate, both theoretically and through solution of an example.

Implicit Numerical Integration of Constrained Equations of Motion via Generalized Coordinate Partitioning

1989 ◽  
Author(s):  
E. J. Haug ◽  
J. Yen
Keyword(s):  
Numerical Integration ◽  
Equations Of Motion ◽  
Integration Algorithm ◽  
Generalized Coordinates ◽  
Multibody Dynamic ◽  
Constraint Set ◽  
Constrained Equations ◽  
Automated Simulation ◽  
Coordinate Partitioning ◽  
Generalized Coordinate

Abstract An implicit, stiffly stable numerical integration algorithm is developed and demonstrated for automated simulation of multibody dynamic systems. The concept of generalized coordinate partitioning is used to parameterize the constraint set with independent generalized coordinates. A stiffly stable, backward difference numerical integration algorithm is applied to determine independent generalized coordinates and velocities. Dependent generalized coordinates, velocities, and accelerations, as well as Lagrange multipliers that account for constraints, are explicitly retained in the formulation to satisfy all of the governing kinematic and dynamic equations. The algorithm is shown to be valid and accurate, both theoretically and through solution of a numerical example.

Direct and Adjoint Sensitivity Analysis of Multibody Systems Using Maggi’s Equations

2013 ◽  
Author(s):  
Daniel Dopico ◽  
Yitao Zhu ◽  
Adrian Sandu ◽  
Corina Sandu
Keyword(s):  
Sensitivity Analysis ◽  
Multibody Systems ◽  
Equations Of Motion ◽  
Third Party ◽  
Adjoint Sensitivity Analysis ◽  
Adjoint Sensitivity ◽  
Dynamics Of Multibody Systems ◽  
Dynamical Optimization ◽  
Analytical Expressions ◽  
Coordinate Partitioning

The importance of the sensitivity analysis of multibody systems for several applications is well known, concretely design optimization based on the dynamics of multibody systems usually requires the sensitivity analysis of the equations of motion. A broad range of methods for the dynamics of multibody systems include the state space formulations based on Maggis equations, nullspace methods or coordinate partitioning. Dynamic sensitivities, when needed, are often calculated by means of finite differences but, depending of the number of parameters involved, this procedure can be very demanding in terms of CPU time and the accuracy obtained can be very poor in many cases. In this paper, several ways to perform the sensitivity analysis are explored and analytical expressions for the direct and adjoint sensitivity analysis of multibody systems are presented, all of them based on Maggi’s formulations. Moreover, two different approaches to the adjoint sensitivity analysis of multibody systems are presented. Although particularized to one formulation, the general expressions provided in the paper, are intended to be easily generalized and applied to any other formulation that can be expressed as an ODE-like system of equations, including penalty formulations. Besides, to check the validity and correctness of the proposed equations, the solutions of all the methods proposed are compared: 1) between them, 2) with the third party code FATODE and 3) with the numerical solution using real and complex perturbations. Finally, all the techniques proposed are applied to the dynamical optimization of a multibody system.

Separated-Form Equations of Motion of Controlled Flexible Multibody Systems

1994 ◽  
Vol 116 (4) ◽  
pp. 702-712 ◽  
Author(s):  
Junghsen Lieh
Keyword(s):  
Multibody Systems ◽  
Virtual Work ◽  
Equations Of Motion ◽  
Second Order ◽  
Active Suspensions ◽  
Physical Term ◽  
Moving Base ◽  
Matrix Expansion ◽  
Generalized Force ◽  
Coordinate Partitioning

This paper introduces a method leading to separated-form formulation of dynamic equations of multibody systems subject to control. The algorithm is derived from the virtual work principle and includes the moving base effects. The elastic members are treated as Euler-Bernoulli beams. Equations of motion are expanded using generalized coordinate partitioning and a Jacobian matrix expansion. The formulation of each physical term is separated, i.e., the inertia matrix, nonlinear coupling vector, generalized force vector and base motion-induced terms are established individually. The formulation is implemented on a workstation using MAPLE. Nonlinear and linearized equations with control are generated in FORTRAN format. The control design adopts second-order models directly. Several examples including a spin-up cantilever beam, an elastic vehicle with active suspensions and an elastic slider-crank mechanism are given. Numerical results for nonlinear and linear spin-up beam models are provided. Simulation for the active vehicle model using second-order control theory is presented.

scholarly journals A brief review of E theory

2016 ◽  
Vol 31 (26) ◽  
pp. 1630043 ◽  
Author(s):  
Peter West
Keyword(s):  
Infinite Number ◽  
Equations Of Motion ◽  
Space Time ◽  
Unified Theory ◽  
Dynamical Equations ◽  
Supergravity Theory ◽  
Maximal Supergravity ◽  
Abdus Salam ◽  
Strings And Branes ◽  
Time Lead

I begin with some memories of Abdus Salam who was my PhD supervisor. After reviewing the theory of nonlinear realisations and Kac–Moody algebras, I explain how to construct the nonlinear realisation based on the Kac–Moody algebra [Formula: see text] and its vector representation. I explain how this field theory leads to dynamical equations which contain an infinite number of fields defined on a space–time with an infinite number of coordinates. I then show that these unique dynamical equations, when truncated to low level fields and the usual coordinates of space–time, lead to precisely the equations of motion of 11-dimensional supergravity theory. By taking different group decompositions of [Formula: see text] we find all the maximal supergravity theories, including the gauged maximal supergravities, and as a result the nonlinear realisation should be thought of as a unified theory that is the low energy effective action for type II strings and branes. These results essentially confirm the [Formula: see text] conjecture given many years ago.

scholarly journals Closed-form time derivatives of the equations of motion of rigid body systems

2021 ◽  
Author(s):  
Andreas Müller ◽  
Shivesh Kumar
Keyword(s):  
Rigid Body ◽  
Closed Form ◽  
Multibody Systems ◽  
Equations Of Motion ◽  
Alternative Formulation ◽  
Dynamics Of Rigid Body ◽  
Control Forces ◽  
And Control ◽  
Derivatives Of ◽  
Insight Into

AbstractDerivatives of equations of motion (EOM) describing the dynamics of rigid body systems are becoming increasingly relevant for the robotics community and find many applications in design and control of robotic systems. Controlling robots, and multibody systems comprising elastic components in particular, not only requires smooth trajectories but also the time derivatives of the control forces/torques, hence of the EOM. This paper presents the time derivatives of the EOM in closed form up to second-order as an alternative formulation to the existing recursive algorithms for this purpose, which provides a direct insight into the structure of the derivatives. The Lie group formulation for rigid body systems is used giving rise to very compact and easily parameterized equations.

A Strategy to Accelerate the Numerical Integration in the Dynamic Simulation of Multibody Systems

1997 ◽  
Author(s):  
Jesús Cardenal ◽  
Javier Cuadrado ◽  
Eduardo Bayo
Keyword(s):  
Multibody Systems ◽  
Equations Of Motion ◽  
Stiff Systems ◽  
Step Size ◽  
Step Method ◽  
Integral Of Motion ◽  
Time Step ◽  
Time Step Size ◽  
Variable Time ◽  
Numerical Integrator

Abstract This paper presents a multi-index variable time step method for the integration of the equations of motion of constrained multibody systems in descriptor form. The basis of the method is the augmented Lagrangian formulation with projections in index-3 and index-1. The method takes advantage of the better performance of the index-3 formulation for large time steps and of the stability of the index-1 for low time steps, and automatically switches from one method to the other depending on the required accuracy and values of the time step. The variable time stepping is accomplished through the use of an integral of motion, which in the case of conservative systems becomes the total energy. The error introduced by the numerical integrator in the integral of motion during consecutive time steps provides a good measure of the local integration error, and permits a simple and reliable strategy for varying the time step. Overall, the method is efficient and powerful; it is suitable for stiff and non-stiff systems, robust for all time step sizes, and it works for singular configurations, redundant constraints and topology changes. Also, the constraints in positions, velocities and accelerations are satisfied during the simulation process. The method is robust in the sense that becomes more accurate as the time step size decreases.

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