Name
Title | ||
|---|---|---|
Designing Decentralized Controllers for Distributed-Air-Jet MEMS-Based Micromanipulators by Reinforcement Learning |
Abstract | ||
|---|---|---|
Distributed-air-jet MEMS-based systems have been proposed to manipulate small parts with high velocities and without any friction problems. The control of such distributed systems is very challenging and usual approaches for contact arrayed system don't produce satisfactory results. In this paper, we investigate reinforcement learning control approaches in order to position and convey an object. Reinforcement learning is a popular approach to nd controllers that are tailored exactly to the system without any prior model. We show how to apply reinforcement learning in a decentralized perspective and in order to address the global-local trade-o. The simulation results demonstrate that the reinforcement learning method is a promising way to design control laws for such distributed systems. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s10846-010-9396-9 | Journal of Intelligent and Robotic Systems |
Keywords | Field | DocType |
MEMS-based actuator array,Smart surface,Decentralized control,Distributed control,Reinforcement learning | Decentralised system,Microelectromechanical systems,Control theory,Control engineering,Engineering,Reinforcement learning | Journal |
Volume | Issue | ISSN |
59 | 2 | 0921-0296 |
Citations | PageRank | References |
9 | 0.78 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laëtitia Matignon | 1 | 88 | 9.43 |
| Guillaume J. Laurent | 2 | 97 | 12.60 |
| Nadine Le Fort-Piat | 3 | 77 | 10.09 |
| Yves-André Chapuis | 4 | 9 | 1.46 |