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This dissertation presents a high-precision positioner with a novel superimposed concentrated-field permanent-magnet matrix. This extended-range multi-axis positioner can generate all 6-DOF (degree-of-freedom) motions with only a single moving part. It is actuated by three planar levitation motors, which are attached on the bottom of the moving part. Three aerostatic bearings are used to provide the suspension force against the gravity for the system. The dynamic model of the system is developed and analyzed. And several control techniques including SISO (single input and single output) and MIMO (multi inputs and multi outputs) controls are discussed in the dissertation. The positioner demonstrates a position resolution of 20 nm and position noise of 10 nm rms in x and y and 15 nm rms in z. The angular resolution around the x-, y-, and z-axes is in sub-microradian order. The planar travel range is 160 mm ?? 160 mm, and the maximum velocity achieved is 0.5 m/s at a 5-m/s2 acceleration, which can enhance the throughput in precision manufacturing. Various experimental results are presented in this dissertation to demonstrate the positioner??s capability of accurately tracking any planar trajectories. Those experimental results verified the potential utility of this 6-DOF high-precision positioner in precision manufacturing and factory automation.

This dissertation is the first attempt to demonstrate the use of magnetic-levitation (maglev) positioners for commercial applications requiring nanopositioning. The key objectives of this research were to devise the control strategies and motion planning to overcome the inherent technical challenges of the maglev systems, and test them on the developed maglev systems to demonstrate their capabilities as the next-generation nanopositioners. Two maglev positioners based on novel actuation schemes and capable of generating all the six-axis motions with a single levitated platen were used in this research. These light-weight single-moving platens have very simple and compact structures, which give them an edge over most of the prevailing nanopositioning technologies and allow them to be used as a cluster tool for a variety of applications. The six-axis motion is generated using minimum number of actuators and sensors. The two positioners operate with a repeatable position resolution of better than 3 nm at the control bandwidth of 110 Hz. In particular, the Y-stage has extended travel range of 5 mm × 5 mm. They can carry a payload of as much as 0.3 kg and retain the regulated position under abruptly and continuously varying load conditions. This research comprised analytical design and development, followed by experimental verification and validation. Preliminary analysis and testing included open-loop stabilization and rigorous set-point change and load-change testing to demonstrate the precision-positioning and load-carrying capabilities of the maglev positioners. Decentralized single-input-single-output (SISO) proportional-integral-derivative (PID) control was designed for this analysis. The effect of actuator nonlinearities were reduced through actuator characterization and nonlinear feedback linearization to allow consistent performance over the large travel range. Closed-loop system identification and order-reduction algorithm were developed in order to analyze and model the plant behavior accurately, and to reduce the effect of unmodeled plant dynamics and inaccuracies in the assembly. Coupling among the axes and subsequent undesired motions and crosstalk of disturbances was reduced by employing multivariable optimal linear-quadratic regulator (LQR). Finally, application-specific nanoscale path planning strategies and multiscale control were devised to meet the specified conflicting time-domain performance specifications. All the developed methodologies and algorithms were implemented, individually as well as collectively, for experimental verification. Some of these applications included nanoscale lithography, patterning, fabrication, manipulation, and scanning. With the developed control strategies and motion planning techniques, the two maglev positioners are ready to be used for the targeted applications.

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Moore’s law states that the number of transistors in an Integrated Circuit (IC) doubles every two years. Ever-increasing performance in mask writing machinery is therefore required being the first step in the manufacturing process. Many factors affect the quality of the end product, with the motion control system playing an important role. This thesis analyzes the performance of the motion controller for the positioning system in a mask writer application. The target motion in the X-axis in the mask writer is by design highly repetitive and predictable. As of today a feedforward-feedback controller is used, tuned for low deviation during writing. In this thesis it is found that the motion control can be improved by exploiting the repetitive nature of the motion task. Two iterative methods are explored, Iterative Feedback Tuning (IFT) and Iterative Learning Control (ILC). IFT is implemented as a parameter optimizing method for the existing Proportional-Integral-Derivative (PID) controller. Given suboptimal initial parameters the algorithm converges to a global minimum using a cost function to minimize total deviation and constraints on the maximum deviation. With the optimized parameter settings an improvement of a 31 % decrease in total deviation is seen compared to the default setting. ILC is implemented as a replacement to the current controller in an exposure motion. With the use of saved data from previous iterations the control signal is updated and refined to better suit the target motion. ILC is a promising method within high precision motion control by virtue of not needing a model of the system and its ability to suppress reoccurring disturbances. The algorithm achieves an improvement of a 94% decrease in total deviation during writing compared to the current controller. However, with this implementation long term stability is not guaranteed. A stable implementation of the algorithm tested on a test rig achieves an improvement of a 79.8% decrease in deviation during writing compared to the current feedforward-feedback controller. Additionally, correlations between parameter values of the current feedback controller and servo characteristics are analyzed to aid in the manual tuning process. Tuning the PID controller for fast rise time decreases the total deviation during writing. The derivative gain in the controller should be high to decrease the overshoot caused by the aggressive controller. This will induce some oscillations into the system, however not at the cost of performance as a result of the smooth motion during writing.