AFM-based Nanomanipulation by Using Robust Integral of NN and Error Sign Control

摘要：

This paper presents a novel control methodology for automatically manipulating nano particles on the substrate by using Atomic Force Microscope (AFM). The interactive forces and dynamics between the tip, particle and substrate are modelled and analysed including the roughness effect of the substrate. Further, the control signal is designed to consist of the robust integral of a neural network (NN) output plus the sign of the error feedback signal multiplied with an adaptive gain. Using the NN-based adaptive force controller, the task of pushing nano particles is demonstrated in simulation environment. Finally, the asymptotical tracking performance of the closed-loop system, boundedness of the NN weight estimates and applied forces are shown by using the Lyapunov-based stability analysis.

作者: Qinmin Yang Jiangang Lu Youxian Sun

作者单位: Department of Control Science and Engineering, Zhejiang University, Hangzhou, China

会议类型: 国际会议

会议名称: The First International Conference on Manipulation,Manufacturing and Measurement on the Nanoscale(第一届3M-NANO国际会议)

会议地点: 长春

会议语种:英文

页码: 1-6

在线出版日期: 2011-08-29（万方平台首次上网日期，不代表论文的发表时间）