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 journalArticle

10 Citations (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 geometry constraints are justified. The non-Gaussian effects due to the stochastic base excitation are also 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)426-432
Number of pages7
JournalJournal of Dynamic Systems, Measurement and Control, Transactions of the ASME
Volume111
Issue number3
DOIs
Publication statusPublished - 1989 Jan 1

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linearization
robots
Linearization
Manipulators
manipulators
Robots
predictions
excitation
Geometry
output
geometry

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Instrumentation
  • Mechanical Engineering
  • Computer Science Applications

Cite this

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