Yang, R., Wang, M., Li, L., Wang, G. and Zhong, C. (2019) Robust Predictive Current Control of PMLSM with Extended State Modeling Based Kalman Filter: For Time-Varying Disturbance Rejection. IEEE Transactions on Power Electronics, 35, 2208-2221.
https://doi.org/10.1109/TPEL.2019.2923631

has been cited by the following article:

• TITLE: Accelerating the Feedback Loop in Scanning Probe Microscopes without Loss of Height Measurement Accuracy by Using Pixel Forecast Methods

  AUTHORS: Robert Köhn, Boris Braun, Kai-Felix Braun

  KEYWORDS: Scanning Probe Microscopy, Feedback Loop, Controller Simulation

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.10 No.4, April 28, 2022

  ABSTRACT: Scanning probe microscopes (SPM) are limited in their speed of data acquisition by the mechanical stability of the scanner. Therefore many types of scanners have been developed to achieve a rigid setup while maintaining an acceptable image size. We have followed here a different path to accelerate data acquisition by improving the feedback loop to achieve the same SPM image quality in a shorter time. While the feedback loop in a scanning probe microscope typically starts to probe a new pixel starting from the previous position, we have reduced the total control time by using an improved starting point for the feedback loop at each pixel. By exploiting the information of the already scanned pixels a forecast for the new pixel is created. We have successfully used several simple methods for a prognosis in MATLAB simulations like one dimensional linear or cubic extrapolation and others. Only scanning tunnelling microscope data from real experiments were used to test the forecasts. A doubling of the speed was achieved in the most favourable cases.