DocumentCode
645976
Title
Motion control for magnetic micro-scale manipulation
Author
Alleyne, Andrew G. ; Schurle, Simone ; Meo, Alessandro ; Nelson, Bradley J.
Author_Institution
Univ. of Illinois, Urbana-Champaign, Urbana, IL, USA
fYear
2013
fDate
17-19 July 2013
Firstpage
784
Lastpage
790
Abstract
This work demonstrates performance improvement in motion control under a particular set of machine system constraints. A high performance industrial magnetic micro-manipulation system, the Minimag, is introduced and modeled with both first principles and system identification. The form of the closed loop controller is constrained by operational bounds and the system software, resulting in limits to achievable performance. A model-based motion control enhancement is developed and implemented using tools from Iterative Learning Control. The resulting performance improvements indicate the benefits of motion control even when the closed loop controller is fixed. Experimental results at two different size scales (500 μm and 4.5μm) are given.
Keywords
adaptive control; closed loop systems; feedforward; industrial manipulators; iterative methods; learning systems; micromanipulators; motion control; Minimag system; closed loop controller; high performance industrial magnetic micromanipulation system; iterative learning control; machine system constraints; magnetic microscale manipulation; model-based motion control enhancement; operational bounds; system software; Feedforward neural networks; Force; Magnetic fields; Magnetic flux; Mathematical model; Trajectory;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (ECC), 2013 European
Conference_Location
Zurich
Type
conf
Filename
6669173
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