Model-less inversion-based iterative control for output tracking: Piezo actuator example

In this article, we propose a model-less inversion- based iterative control (MIIC) approach for high-speed output tracking in repetitive applications such as the lateral scanning during atomic force microscope (AFM) imaging. The MIIC algorithm extends the inversion-based iterative control (IIC) technique and the enhanced inversion-based iterative control (EIIC) technique. The main contribution of this article is the development of the MIIC algorithm to eliminate the modeling process while further enhancing the output tracking performance. We explicitly consider the disturbance and/or measurement noise effect in the convergence analysis of the MIIC algorithm. It is shown that convergence can be reached in one iteration step if the noise/disturbance effect is negligible; Or, the input error can be quantified by the disturbance/noise to signal ratio (NSR, relative to the desired trajectory). The MIIC is applied to a piezo scanner on an atomic force microscope, and experimental results are presented to demonstrate the efficacy of the MIIC technique.

[1]  Jayati Ghosh,et al.  A pseudoinverse-based iterative learning control , 2002, IEEE Trans. Autom. Control..

[2]  S Devasia,et al.  CONTROL ISSUES IN HIGH‐SPEED AFM FOR BIOLOGICAL APPLICATIONS: COLLAGEN IMAGING EXAMPLE , 2004, Asian journal of control.

[3]  Roland Wiesendanger,et al.  Scanning Probe Microscopy and Spectroscopy: Related scanning probe methods , 1994 .

[4]  Qingze Zou,et al.  Iterative Control Approach to Compensate for Both the Hysteresis and the Dynamics Effects of Piezo Actuators , 2007, IEEE Transactions on Control Systems Technology.

[5]  F. Filhol,et al.  Resonant micro-mirror excited by a thin-film piezoelectric actuator for fast optical beam scanning , 2005 .

[6]  H. Schenk,et al.  Scanning micro-mirrors: from bar-code scanning to spectroscopy , 2005, SPIE Optics + Photonics.

[7]  Gjerrit Meinsma,et al.  On admissible pairs and equivalent feedback - Youla parameterization in iterative learning control , 2006, Autom..

[8]  Kevin L. Moore,et al.  Iterative learning control: A survey and new results , 1992, J. Field Robotics.

[9]  Masayoshi Tomizuka,et al.  Design requirements and reference trajectory generation for a copier paperpath , 2001, 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings (Cat. No.01TH8556).

[10]  Qingze Zou,et al.  Iterative control of dynamics-coupling-caused errors in piezoscanners during high-speed AFM operation , 2005, IEEE Transactions on Control Systems Technology.

[11]  Shiuh-Jer Huang,et al.  Development of a multi-optical source rapid prototyping system , 2005 .

[12]  Qingze Zou,et al.  Iterative control approach to high-speed force-distance curve measurement using AFM: time-dependent response of PDMS example. , 2008, Ultramicroscopy.

[13]  Péter Gáspár,et al.  Iterative model-based mixed H2/Hinfinity control design , 1998 .

[14]  Qingze Zou,et al.  Iteration-based Scan-Trajectory Design and Control with Output-Oscillation Minimization: Atomic Force Microscope Example , 2007, 2007 American Control Conference.