Application of WINROSA for Controller Adaptation in Robotics and Classification in Quality Control

Abstract

This paper presents two applications of the WINROSA software tool. In the first application a data-based generated fuzzy modul is used to adapt the parameters of the position controller of an industrial robot to optimise the continuous path accuracy. It is shown how to learn from good and poor control strategies. The second application is the classification of automatic gear boxes by 149 characteristics. It is demonstrated that a data-based generated fuzzy modul is a promising approach for handling this very complex problem. A new method for complexity reduction is used to reduce the number of necessary process characteristics by analysing their relevance for the classification.