Self-organising locally interpolating maps in control engineering

The work is motivated by problems during automated motion control of mobile microrobots. Microrobots can manipulate objects in the sub-micrometre-range if the actuator controller is correspondingly accurate. A data-based learning controller model is implemented with the Self-Organising Locally Interpolating Map (SOLIM). SOLIM includes a new method that continuously and interpretably maps from a grid of input support vectors, e.g. a robot's velocity, to a grid of output support vectors, e.g. corresponding control commands. Moreover, a learning algorithm has been developed, which iteratively adapts the output support vectors such that the SOLIM map represents an inverse model of the unknown system to be controlled. The most important properties of the SOLIM approach have been proven in simulations and during position control of mobile microrobot platforms.

Level thesis:degree_level

thesis.doctoral

Grantor dc:publisher

Universität Oldenburg

Year

2007

Author dc:creator

• Hülsen, Helge

• [Keine Schlagwörter von Autor/in vergeben.]

Repository record source_url

http://oops.uni-oldenburg.de/25

OAI identifier oai:identifier

oai:oops.uni-oldenburg.de:25