A Neural Approach for the Control of Piezoelectric Micromanipulation Robots
Micromanipulation has become an issue of primary importance in industry and biomedicine, since human manual capabilities are restricted to certain tolerances. The manipulation of biological cells or the assembly of a complete microsystem composed of different microcomponents are examples of the application of piezoelectric-driven microrobots. An automated microrobot-based micromanipulation desktop-station is developed by an interdisciplinary group at the University of Karlsruhe. The process of assembly takes place in the field of view of a light optical microscope. This paper focuses on motion control problems of the microrobots. The ability of an intelligent microsystem to adapt itself to the process requirements is of great importance, especially for assembly robots. The microrobots must be able to operate in a partially defined environment and to ensure reasonable behaviour in unpredicted situations. A neural control concept based on a reference model approach is proposed as a solution. It is shown, that the neural controller is able to learn the desired behaviour. It considerably outperforms an analytically designed linear controller. This is demonstrated both in simulation and in the real environment.