Prediction of stationary response of robot manipulators under stochastic base and external excitations - statistical linearization approach.

Ren-Jung Chang, G. E. Young

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

The Lagrangian dynamic equation and statistical linearization for an n-dimensional manipulator subjected to both stochastic base and external excitations and geometric constraints in states are derived. The effects of utilizing a truncated Gaussian density in the linearization due to the geometric constraints is justified. The non-Gaussian effects due to the stochastic base excitation are quantified to justify the accuracy in the prediction of the stationary output variances. Two examples of robot manipulators are selected to illustrate the accuracy of predicted variances by the linearization techniques.

Original languageEnglish
Pages (from-to)1357-1363
Number of pages7
JournalProceedings of the American Control Conference
Volume88 pt 1-3
Publication statusPublished - 1988 Dec 1

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Linearization
Manipulators
Robots

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

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title = "Prediction of stationary response of robot manipulators under stochastic base and external excitations - statistical linearization approach.",
abstract = "The Lagrangian dynamic equation and statistical linearization for an n-dimensional manipulator subjected to both stochastic base and external excitations and geometric constraints in states are derived. The effects of utilizing a truncated Gaussian density in the linearization due to the geometric constraints is justified. The non-Gaussian effects due to the stochastic base excitation are quantified to justify the accuracy in the prediction of the stationary output variances. Two examples of robot manipulators are selected to illustrate the accuracy of predicted variances by the linearization techniques.",
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N2 - The Lagrangian dynamic equation and statistical linearization for an n-dimensional manipulator subjected to both stochastic base and external excitations and geometric constraints in states are derived. The effects of utilizing a truncated Gaussian density in the linearization due to the geometric constraints is justified. The non-Gaussian effects due to the stochastic base excitation are quantified to justify the accuracy in the prediction of the stationary output variances. Two examples of robot manipulators are selected to illustrate the accuracy of predicted variances by the linearization techniques.

AB - The Lagrangian dynamic equation and statistical linearization for an n-dimensional manipulator subjected to both stochastic base and external excitations and geometric constraints in states are derived. The effects of utilizing a truncated Gaussian density in the linearization due to the geometric constraints is justified. The non-Gaussian effects due to the stochastic base excitation are quantified to justify the accuracy in the prediction of the stationary output variances. Two examples of robot manipulators are selected to illustrate the accuracy of predicted variances by the linearization techniques.

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