Demo Data from EDBT 2026 / reviewers in the wild / expert
Kiu Ling Pau
dblp:37/1997
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
adaptive control |
0.0 | 1 | 1999 | Adaptive Control of Time-Varying Mechanical Systems: Modeling, Controller Design and Experiments · ICRA 1999 |
Robotics › Motion planning and robot control › robot control › adaptive control
parameter adaptation |
0.0 | 1 | 1999 | Adaptive Control of Time-Varying Mechanical Systems: Modeling, Controller Design and Experiments · ICRA 1999 |
Robotics › Motion planning and robot control
robot dynamics |
0.0 | 1 | 1999 | Adaptive Control of Time-Varying Mechanical Systems: Modeling, Controller Design and Experiments · ICRA 1999 |
Methods — techniques the papers use, named apart from their topics
adaptive control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1999 | Adaptive Control of Time-Varying Mechanical Systems: Modeling, Controller Design and ExperimentsabstractIn this work, we consider adaptive control of time-varying mechanical systems. First, we derive the dynamics of time-varying mechanical systems under the assumption that the generalized constraints on the system do not depend on time but the system parameters such as masses and payloads are time-varying. A compact parameterization of the dynamics of the system is obtained based on the rate of change of parameters being a polynomial in time. Based on this parameterization, adaptation laws for the time-varying parameters is proposed. To test the proposed adaptive controllers, an experimental platform consisting of a two-link robot with a time-varying payload is designed. The designed experimental platform mimics pouring/filling operations in industry, where the payload is time-varying. Experimental results demonstrate the effectiveness of the proposed adaptive control designs. Prabhakar R. Pagilla, Kiu Ling Pau, Biao Yu |
ICRA | 2 |