Publication

Data-Driven Controller Design for Atomic-Force Microscopy

Alireza Karimi, Georg Fantner, Adrian Pascal Nievergelt, Christoph Manuel Kammer
2017
Conference Papers

Abstract

A novel method to design data-driven, fixed-structure controllers with H2 and H∞ performance objectives is presented. The control design problem is transformed into a convex optimization problem with linear matrix inequality constraints, which can be solved efficiently with standard solvers. The method is used to design a data-driven controller for an atomic-force microscope. The closed-loop performance of the calculated controller is validated on a real setup.

Official source

https://infoscience.epfl.ch/entities/publication/2c77d7ae-0f0a-4458-88d2-7a6eff9a3e00

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Data-Driven Controller Design for Atomic-Force Microscopy

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