Development of a modular control algorithm for high precision positioning systems

buir.advisorÇakmakcı, Melih
dc.contributor.authorUlu, Nurcan Geçer
dc.date.accessioned2016-01-08T18:20:22Z
dc.date.available2016-01-08T18:20:22Z
dc.date.issued2012
dc.departmentDepartment of Mechanical Engineeringen_US
dc.descriptionAnkara : The Department of Mechanical Engineering and the Graduate School of Engineering and Science of Bilkent University, 2012.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2012.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractIn 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.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityUlu, Nurcan Geçeren_US
dc.format.extentxvi, 82 leaves, illustrationsen_US
dc.identifier.urihttp://hdl.handle.net/11693/15543
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectIterative learning controlen_US
dc.subjectcross-coupled controlen_US
dc.subjectprecision motion controlen_US
dc.subject.lccTJ217.5 .U48 2012en_US
dc.subject.lcshIntelligent control systems.en_US
dc.subject.lcshMotion control devices.en_US
dc.subject.lcshIterative methods (Mathematics)en_US
dc.titleDevelopment of a modular control algorithm for high precision positioning systemsen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
0006273.pdf
Size:
8.77 MB
Format:
Adobe Portable Document Format