Abstract
Robot control strategies utilize the dynamic robot model to decouple the joints and specify the closed-loop response. The implementation of model-based control algorithms, however, is based upon the on-line evaluation of robot dynamics. This evaluation, which is on the order of milliseconds for typical industrial manipulators, introduces discretization errors (in addition to potential modeling and parameter errors) and degrades performance. In this paper, a novel supervisory structure is introduced to ameliorate the problem. The proposed structure incorporates nonlinearity compensation at the joint level (through a computer-control feedback algorithm); and performance monitoring at the task level (through discrete-time predictors. Preliminary simulation experiments demonstrate the feasibility and applicability of the approach.
| Original language | English |
|---|---|
| Title of host publication | Unknown Host Publication Title |
| Publisher | ISA (Robotics and Expert Systems v 3) |
| Pages | 201-206 |
| Number of pages | 6 |
| ISBN (Print) | 1556170262 |
| Publication status | Published - 1987 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
SUPERVISORY ROBOT CONTROL VIA NONLINEARITY COMPENSATION AND PERFORMANCE MONITORING. / Tourassis, Vassilios D.
Unknown Host Publication Title. ISA (Robotics and Expert Systems v 3), 1987. p. 201-206.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - SUPERVISORY ROBOT CONTROL VIA NONLINEARITY COMPENSATION AND PERFORMANCE MONITORING.
AU - Tourassis, Vassilios D.
PY - 1987
Y1 - 1987
N2 - Robot control strategies utilize the dynamic robot model to decouple the joints and specify the closed-loop response. The implementation of model-based control algorithms, however, is based upon the on-line evaluation of robot dynamics. This evaluation, which is on the order of milliseconds for typical industrial manipulators, introduces discretization errors (in addition to potential modeling and parameter errors) and degrades performance. In this paper, a novel supervisory structure is introduced to ameliorate the problem. The proposed structure incorporates nonlinearity compensation at the joint level (through a computer-control feedback algorithm); and performance monitoring at the task level (through discrete-time predictors. Preliminary simulation experiments demonstrate the feasibility and applicability of the approach.
AB - Robot control strategies utilize the dynamic robot model to decouple the joints and specify the closed-loop response. The implementation of model-based control algorithms, however, is based upon the on-line evaluation of robot dynamics. This evaluation, which is on the order of milliseconds for typical industrial manipulators, introduces discretization errors (in addition to potential modeling and parameter errors) and degrades performance. In this paper, a novel supervisory structure is introduced to ameliorate the problem. The proposed structure incorporates nonlinearity compensation at the joint level (through a computer-control feedback algorithm); and performance monitoring at the task level (through discrete-time predictors. Preliminary simulation experiments demonstrate the feasibility and applicability of the approach.
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M3 - Conference contribution
SN - 1556170262
SP - 201
EP - 206
BT - Unknown Host Publication Title
PB - ISA (Robotics and Expert Systems v 3)
ER -