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Distributed optimization for multi-object manipulation by shaping spatial force fields
Author: Martin Gurtner
This thesis addresses three topics related to feedback manipulation through shaping force fields: position measurement, modeling of force fields, and force model inversion through distributed optimization. The first two topics focus specifically on dielectrophoresis. The third topic covers manipulation using more general force fields. The thesis presents a new sensor for measuring the 3D positions of micro-objects in real time with sufficient accuracy for feedback control. It also introduces a control-oriented model of dielectrophoretic force that can be evaluated in real time and thus is suitable for feedback control. This model is verified through experiments. The thesis proposes a distributed optimization algorithm based on ADMM for finding electric potentials that produce a desired dielectrophoretic force field, a process called model inversion. The distributed algorithm can be applied to manipulation using other physical force fields and is tested on dielectrophoresis, magnetophoresis, and acoustophoresis. Additionally, the thesis presents a compact dielectrophoretic manipulation platform that incorporates the proposed position sensor, dielectrophoretic model, and optimization-based model inversion, as well as the capability to observe manipulated objects using lensless digital holography.