Abstract
This work builds upon a framework for improving trajectory flexibility in systems controlled by Iterative Learning Control (ILC). Here we focus on positioning systems, decomposing a class of trajectories into motion primitives, termed basis tasks. The correct input signal for each basis task is identified in a training routine with ILC. The main development of this paper is a framework to intelligently apply these basis task specific input signals using an adaptation of bumpless transfer techniques. Bumpless transfer is reoriented to seamlessly transition between open-loop ILC signals without attenuating signal content away from the transition points. Experimental results display the effectiveness of the proposed approach on a serial planar positioning robot. Two conditions on basis task sequencing are tested. One which satisfies constraints imposed by previous work, and a relaxed trajectory constraint case designed to further explore trajectory flexibility. Bumpless transfer recovers some of the performance lost by constraint relaxation.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 2011 American Control Conference, ACC 2011 |
| Pages | 4305-4311 |
| Number of pages | 7 |
| State | Published - 2011 |
| Event | 2011 American Control Conference, ACC 2011 - San Francisco, CA, United States Duration: Jun 29 2011 → Jul 1 2011 |
Other
| Other | 2011 American Control Conference, ACC 2011 |
|---|---|
| Country | United States |
| City | San Francisco, CA |
| Period | 6/29/11 → 7/1/11 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
Bumpless transfer for a flexible adaptation of iterative learning control. / Hoelzle, David J.; Alleyne, Andrew G.; Wagoner Johnson, Amy J.
Proceedings of the 2011 American Control Conference, ACC 2011. 2011. p. 4305-4311 5991452.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Bumpless transfer for a flexible adaptation of iterative learning control
AU - Hoelzle, David J.
AU - Alleyne, Andrew G.
AU - Wagoner Johnson, Amy J.
PY - 2011
Y1 - 2011
N2 - This work builds upon a framework for improving trajectory flexibility in systems controlled by Iterative Learning Control (ILC). Here we focus on positioning systems, decomposing a class of trajectories into motion primitives, termed basis tasks. The correct input signal for each basis task is identified in a training routine with ILC. The main development of this paper is a framework to intelligently apply these basis task specific input signals using an adaptation of bumpless transfer techniques. Bumpless transfer is reoriented to seamlessly transition between open-loop ILC signals without attenuating signal content away from the transition points. Experimental results display the effectiveness of the proposed approach on a serial planar positioning robot. Two conditions on basis task sequencing are tested. One which satisfies constraints imposed by previous work, and a relaxed trajectory constraint case designed to further explore trajectory flexibility. Bumpless transfer recovers some of the performance lost by constraint relaxation.
AB - This work builds upon a framework for improving trajectory flexibility in systems controlled by Iterative Learning Control (ILC). Here we focus on positioning systems, decomposing a class of trajectories into motion primitives, termed basis tasks. The correct input signal for each basis task is identified in a training routine with ILC. The main development of this paper is a framework to intelligently apply these basis task specific input signals using an adaptation of bumpless transfer techniques. Bumpless transfer is reoriented to seamlessly transition between open-loop ILC signals without attenuating signal content away from the transition points. Experimental results display the effectiveness of the proposed approach on a serial planar positioning robot. Two conditions on basis task sequencing are tested. One which satisfies constraints imposed by previous work, and a relaxed trajectory constraint case designed to further explore trajectory flexibility. Bumpless transfer recovers some of the performance lost by constraint relaxation.
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UR - http://www.scopus.com/inward/citedby.url?scp=80053158580&partnerID=8YFLogxK
M3 - Conference contribution
SN - 9781457700804
SP - 4305
EP - 4311
BT - Proceedings of the 2011 American Control Conference, ACC 2011
ER -