Chen, Chih-LiehChih-LiehChenWu, Jim-WeiJim-WeiWuLin, Yi-TingYi-TingLinLo, Yu-TingYu-TingLoLI-CHEN FU2020-05-042020-05-04201307431546https://scholars.lib.ntu.edu.tw/handle/123456789/489000https://www.scopus.com/inward/record.uri?eid=2-s2.0-84902305526&doi=10.1109%2fCDC.2013.6759906&partnerID=40&md5=fa2aabcdf32ce35049b9d39a58741e2cAtomic force microscopy (AFM) is a useful measurement instrument which can build three-dimensional topography image of conductive and nonconductive samples at high resolution. However, due to the scanning trajectory of conventional AFM, the induced mechanical resonance of the scanner and uninteresting area scanning would limit the scanning speed. In this paper, we improve these problems with our designed AFM system from three aspects. First, the sinusoidal trajectory is applied to AFM lateral scanning rather than the traditional raster trajectory, so the scanning rate can be increased without inducing vibration of the lateral scanner. Second, with this well-known trajectory, the neural network complementary sliding mode controller (NNCSMC) based on internal model principle (IMP) is proposed to achieve high precision scanning and to cope with the system parameter uncertainties and external disturbance. Finally, with the aid of an auxiliary optical microscopy which is usually used for calibration, a simple path planning method can be adopted to focus the scanning on the samples for the purpose of removing the redundant background scanning for shortening the total scanning time. Experimental results are provided to demonstrate the effectiveness of the proposed method. © 2013 IEEE.[SDGs]SDG11Atomic force microscopy (AFM); Complementary sliding mode control; Internal model principle; Local scanning; Neural network; Sinusoidal trajectoryAtomic force microscopy; Neural networks; Optical data storage; Optical microscopy; Sliding mode control; Topography; Trajectories; External disturbances; Internal model principle; Measurement instruments; Mechanical resonance; Parameter uncertainty; Sinusoidal trajectories; Sliding mode controller; Three-dimensional topography; Scanningconference paper10.1109/CDC.2013.67599062-s2.0-84902305526