Data-driven control in atomic force microscopy using a genetic algorithm

Increasing the scanning speed in Atomic Force Microscopy (AFM) relies on improving the tracking performance in the vertical direction of motion. The lightly damped resonances of piezo-actuators utilized in AFM nano-positioning stages hinder the maximum achievable bandwidth in tracking sample topographies. A high-order linear controller is proposed as solution. This controller is placed in series with the conventional proportional-integral (PI) controller in AFM to cancel the resonances and push the bandwidth limits to higher values. An optimization problem is formed based on the frequency response of the actuator and the desired performance characteristics for the system. The controller is shaped by solving this problem with a genetic algorithm. Implementing the proposed controller on several AFM scanners shows its effectiveness in improving the tracking bandwidth and hence, increasing the achievable scan speed.