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 language | English |
|---|---|
| Pages (from-to) | 426-432 |
| Number of pages | 7 |
| Journal | Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME |
| Volume | 111 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 1989 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Information Systems
- Instrumentation
- Mechanical Engineering
- Computer Science Applications
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Prediction of stationary response of robot manipulators under stochastic base and external excitations-statistical linearization approach. / Chang, Ren-Jung; Young, G. E.
In: Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, Vol. 111, No. 3, 01.01.1989, p. 426-432.Research output: Contribution to journal › Article
TY - JOUR
T1 - Prediction of stationary response of robot manipulators under stochastic base and external excitations-statistical linearization approach
AU - Chang, Ren-Jung
AU - Young, G. E.
PY - 1989/1/1
Y1 - 1989/1/1
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 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.
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 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.
UR - http://www.scopus.com/inward/record.url?scp=0024731533&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0024731533&partnerID=8YFLogxK
U2 - 10.1115/1.3153071
DO - 10.1115/1.3153071
M3 - Article
VL - 111
SP - 426
EP - 432
JO - Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME
JF - Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME
SN - 0022-0434
IS - 3
ER -