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In this paper, we present the design, fabrication, and testing of a moving magnet actuator (MMA) for large range (∼10mm) nanopositioning. MMAs are direct-drive, single-phase electromagnetic linear actuators that provide frictionless and backlash-free motion. These qualities, along with an adequate motion range, make MMAs promising candidates for large range nanopositioning. In this work, we identify actuator- and system-level performance criteria and associated design tradeoffs, and use this knowledge to systematically and concurrently design an MMA and a double parallelogram flexure bearing. The resulting actuator provides a force output per unit square root power of 4.56N/W, better than 9% force uniformity with respect to stroke, and a low moving mass of 106g. An integrated thermal management system is also incorporated as part of the actuator in order to mitigate the heat dissipated from the MMA coils. The overall single-axis motion system was fabricated and tested to demonstrate a 36Hz open-loop bandwidth and less than 4nm (RMS) steady-state positioning noise over a 10mm motion range. Preliminary closed-loop design and testing highlight the potential of the proposed actuator in nanopositioning.

This paper presents the control system design and tracking performance for a large range single-axis nanopositioning system that is based on a moving magnet actuator and a flexure bearing. While the physical system is designed to be free of friction and backlash, the nonlinearities in the electromagnetic actuator as well as the harmonic distortion in the drive amplifier degrade the tracking performance for dynamic commands. It is shown that linear feedback and feedforward proves to be inadequate to overcome these nonlinearities. This is due to the low open-loop bandwidth of the physical system, which limits the achievable closed-loop bandwidth given actuator saturation concerns. For periodic commands, like those used in scanning applications, the component of the tracking error due to the system nonlinearities exhibits a deterministic pattern and repeats every period. Therefore, a phase lead type iterative learning controller (ILC) is designed and implemented in conjunction with linear feedback and feedforward to reduce this periodic tracking error by more than two orders of magnitude. Experimental results demonstrate the effectiveness of ILC in achieving 10 nm RMS tracking error over 8 mm motion range in response to a 2 Hz band-limited triangular command. This corresponds to a dynamic range of more than 10 5 for speeds up to 32 mm/s, one of the highest reported in the literature so far, for a cost-effective desktop-sized single-axis motion system. Published by Elsevier Inc.