Artificial neural network based controller for fast and accurate atomic force microscope - Othman, Yahya Sherif (Kulliyyah of Engineering, International Islamic University Malaysia, 2013)
Despite its wide use in Atomic Force Microscopies (AFM), the performance of Piezoelectric Tube Scanner is limited by vibration and inherent nonlinearities that include hysteresis and creep. These limitations restrict the use of Piezoelectric Tube Scanner in fast and accurate operation of atomic force microscopies. Vibration is a linear problem that can be solved efficiently using conventional techniques. However hysteresis that is a nonlinear problem cannot be handled efficiently using these conventional techniques. In this research work, a new nonlinear model of Piezoelectric Tube Scanner has been developed for simulation analysis. Two intelligent approaches using Artificial Neural Network (ANN) have been developed to overcome these hysteresis and vibration limitations. First, a time based ANN control scheme is developed for hysteresis compensation, the results shows that this control approach has efficiently reduced hysteresis effect but not vibration. Hence, another control scheme based on frequency domain analysis has been developed. The results proved the efficiency of the frequency based approach by reducing hysteresis effect and controlling vibration.