Development of a modular control algorithm for high precision positioning systems
Author
Ulu, Nurcan Geçer
Advisor
Çakmakcı, Melih
Date
2012Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
In the last decade, micro/nano-technology has been improved significantly.
Micro/nano-technology related products started to be used in consumer market
in addition to their applications in the science and technology world. These
developments resulted in a growing interest for high precision positioning systems
since precision positioning is crucial for micro/nano-technology related applications.
With the rise of more complex and advanced applications requiring smaller
parts and higher precision performance, demand for new control techniques that
can meet these expectations is increased.
The goal of this work is developing a new control technique that can meet
increased expectations of precision positioning systems. For this purpose, control
of a modular multi-axis positioning system is studied in this thesis. The multiaxis
precision positioning system is constructed by assembling modular single-axis
stages. Therefore, a single-axis stage can be used in several configurations. Model
parameters of a single-axis stage change depending on which axis it is used for.
For this purpose, an iterative learning controller is designed to improve tracking
performance of a modular single-axis stage to help modular sliders adapting to
repeated disturbances and nonlinearities of the axis they are used for. When
modular single-axis stages are assembled to form multi-axis systems, the interaction
between the axes should be considered to operate stages simultaneously. In
order to compensate for these interactions, a multi input multi output (MIMO)
controller can be used such as cross-coupled controller (CCC). Cross-coupled controller
examines the effects between axes by controlling the contour error resulting
in an improved contour tracking.
In this thesis, a controller featuring cross-coupled control and iterative learning
control schemes is presented to improve contour and tracking accuracy at the
same time. Instead of using the standard contour estimation technique proposed
with the variable gain cross-coupled control, presented control design incorporates
a computationally efficient contour estimation technique. In addition to that,
implemented contour estimation technique makes the presented control scheme
more suitable for arbitrary nonlinear contours and multi-axis systems. Also, using
the zero-phase filtering based iterative learning control results in a practical design
and an increased applicability to modular systems. Stability and convergence of
the proposed controller has been shown with the necessary theoretical analysis.
Effectiveness of the control design is verified with simulations and experiments
on two-axis and three-axis positioning systems. The resulting controller is shown
to achieve nanometer level contouring and tracking performance.