A novel learning control strategy for hysteresis and vibration of piezo-scanners

Piezoelectric actuators have been widely utilized in micro/nano systems due to the high positioning resolution. A typical instance is piezo-scanners equipped in scanning probe microscopes (SPM) to implement nanoscale measurement and manipulation for various samples. However, the inherent hysteresis and structural vibration of a piezo-scanner largely limit its positioning accuracy and bandwidth, as a result, current SPM has to be operated under comparatively low frequency, which does not meet the requirements of the highly developing nanotechnology. In this paper, a novel learning control strategy is proposed to mitigate the effects of hysteresis and vibration, so that to enable a piezo-scanner to achieve good tracking for periodic trajectories. Lyapunov technique is utilized to analyze the performance of the control algorithm, which proves that it guarantees global stability for the closed-loop error system. A simulation example is included to demonstrate that the designed control law reduces the effects of vibration and hysteresis of piezo-scanners remarkably.