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Scanning Tunneling Microscope Control: A Self-Tuning PI Controller Based on Online Local Barrier Height Estimation | IEEE Journals & Magazine | IEEE Xplore

Scanning Tunneling Microscope Control: A Self-Tuning PI Controller Based on Online Local Barrier Height Estimation


Abstract:

We identify the dynamics of a scanning tunneling microscope (STM) in closed loop and show that the plant dc gain is proportional to the square root of local barrier heigh...Show More

Abstract:

We identify the dynamics of a scanning tunneling microscope (STM) in closed loop and show that the plant dc gain is proportional to the square root of local barrier height (LBH), a quantum mechanical property of the sample and/or tip that affects the tunneling current. We demonstrate that during a scan, the LBH may undergo significant variations and this can adversely affect the closed-loop stability if the controller parameters remain fixed. Feedback instabilities increase the risk of tip-sample crash in STMs. In order to improve the closed-loop performance, we estimate the LBH, on the fly, and use that to adaptively tune the proportional-integral (PI) controller parameters. Experimental results obtained with the self-tuning PI controller confirm the improved STM performance compared to the conventional fixed-gain PI controller. Additional experiments confirm effectiveness of the proposed method in extending the tip lifetime by lowering the chance of a tip/sample crash.
Published in: IEEE Transactions on Control Systems Technology ( Volume: 27, Issue: 5, September 2019)
Page(s): 2004 - 2015
Date of Publication: 28 June 2018

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