A Review of Feedforward Control Approaches in Nanopositioning for High-Speed SPM

Abstract

Control can enable high-bandwidth nanopositioning needed to increase the operating speed of scanning probe microscopes (SPMs). High-speed SPMs can substantially impact the throughput of a wide range of emerging nanosciences and nanotechnologies. In particular, inversion-based control can find the feedforward input needed to account for the positioning dynamics and, thus, achieve the required precision and bandwidth. This article reviews inversion-based feedforward approaches used for high-speed SPMs such as optimal inversion that accounts for model uncertainty and inversion-based iterative control for repetitive applications. The article establishes connections to other existing methods such as zero-phase-error-tracking feedforward and robust feedforward. Additionally, the article reviews the use of feedforward in emerging applications such as SPM-based nanoscale combinatorial-science studies, image-based control for subnanometer-scale studies, and imaging of large soft biosamples with SPMs.

Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification

“…For servo systems, the main performance improvement is in general obtained by using feedforward to compensate for the reference signal. Relevant examples of feedforward control include model-based feedforward, see, e.g., Zhong, Pao, and de Callafon (2012), Clayton, Tien, Leang, Zou, and Devasia (2009) and Butterworth, Pao, and Abramovitch (2012), and Iterative Learning Control (ILC), see, e.g., Bristow, Tharayil, and Alleyne (2006) and Moore (1993).…”

Adaptive feed-forward hysteresis compensation for piezoelectric actuators

“…The relations in (4) can then be used to find the parameters to be used in this hysteresis compensation scheme. The parameters in the model given by (2) and (3) cannot be identified, as it is not possible to measure the signal w h . The parameter identification scheme is described in detail in Appendix A.…”

“…For low-speed reference trajectory tracking, the largest error contribution comes from the hysteresis and creep nonlinearities. 1,2 The error introduced by these nonlinearities can be reduced by using feed-forward or feedback control, or by driving the actuator by charge rather than voltage.…”

Analog Robust Repetitive Control for Nanopositioning Using Bucket Brigade Devices

“…RC can easily be implemented digitally using a pure time-delay, a memory buffer, inside of a positive feedback loop (Inoue et al, 1981). Compared to traditional feedback and feedforward control laws (Clayton et al, 2009;Devasia et al, 2007), the tracking error of RC diminishes as the number of operating periods increases. The control law generally requires only the period of the reference trajectory to be known (Inoue et al, 1981).…”

“…Nanopositioners employed in applications that include scanning probe microscopy (SPM) require tracking of fast periodic reference trajectories with high accuracy Clayton et al, 2009). Periodic reference trajectories occur in both imaging and manipulation applications of SPM equipment.…”