Nonlinear Control Techniques for the Atomic Force Microscope System

Abstract

In this paper, three nonlinear control techniques are proposed for an atomic force microscope system. Initially, a learning-based control algorithm is developed for the microcantilever sample system that achieves asymptotic cantilever tip tracking for periodic trajectories. Specifically, the hybrid control approach utilizes a combination of a learning-based feedforward term to compensate for periodic dynamics while hign-gain terms are utilized to account for non-periodic dynamics. An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters. Lastly, a nonlinear controller coupled with a nonlinear observer is designed to provide for asymptotic tracking and interaction force identification unders a set of assumptions. Simulation results are provided to illustrate the e?cacy and performance of the control strategies.

Publication

For more information concerning this research, please refer to the following publication:

Y. Fang, M. Feemster, D. M. Dawson, and N. Jalili, "Nonlinear Control Techniques for the Atomic Force Microscope System", Proc. of the ASME International Mechanical Engineering Congress and Exposition, November, 2002, to appear.

References