Enhanced Tracking for Nanopositioning Systems Using Feedforward/Feedback Multivariable Control Design

Abstract

This paper proposes a systematic synthesis methodology for a combined feedforward/feedback architecture to control multiple-input, multiple-output nanopositioning systems. Coprime factorization of the open loop model is used to design the reference and feedforward filters of the proposed control scheme to achieve enhanced tracking, eliminate the limitation of the feedback on tracking performance, and increase the bandwidth of the closed-loop system. Two types of coprime factorization, namely inner-outer factorization and normalized coprime factorization are discussed. A case study based on hardware experiment is presented to analyze the proposed control architecture and demonstrate its superiority over feedback-only control. In addition to the no-load case, the performance of the system is also tested with loads on the nanopositioning stage.