Xiaokun Dong

Note: A novel atomic force microscope fast imaging approach: Variable-speed scanning

Imaging speed is one of the key factors limiting atomic force microscopes (AFM) wide applications. To improve its performance, a variable-speed scanning (VSS) method is designed in this note for an AFM. Specifically, in the VSS mode, the scanning speed is tuned online according to the feedback information to properly distribute imaging time along sample surface. Furthermore, some practical mechanism is proposed to determine the best time of moving the AFM tip to the next scanned point. The contrast experiment results show that the VSS method speeds up the imaging rate while ensuring image quality.

System modeling of an AFM System in Z-axis

Motivated by increasing the scanning performance of the atomic force microscope (AFM), many efforts have been made to analyze the system behavior of an AFM system, mainly in Z-axis, and then to develop more advanced controllers. However, most of the previously derived models involve complex physical or mathematical analysis, and many parameters need to be identified for actual application. In this paper, an empirical model is obtained for the Z-axis dynamics of an AFM system by utilizing experimental data. Specifically, the model consists of a dynamical component and multiple static gains. As introduced in the paper, the N4SID algorithm is first employed to derive the dynamical part based on input-output data. Then the static gains of the piezo-actuator are calibrated experimentally. It can be seen from the experimental data that the main source of time delay in Z-axis is the finite retraction/protraction velocity of the piezo-actuator.

AM-AFM System Analysis and Output Feedback Control Design With Sensor Saturation

This paper analyzes the dynamics of an amplitude-modulation atomic force microscopy (AM-AFM) system, and designs a novel output feedback robust adaptive control (OFRAC) law to improve the scanning performance of the AM-AFM system. That is, a control-oriented reduced model is proposed to approximate the mapping from tip-sample separation to oscillation amplitude, whose accuracy is verified by experimental results. Considering the facts that the parameters of an AM-AFM system vary with different combinations of piezo-scanner and cantilever as well as detected samples, and measurement saturation occurs frequently in dynamic AFM systems, an OFRAC strategy for the piezo-scanner is designed to keep the oscillation amplitude of the cantilever staying at the desired setpoint under various complex situations. It is shown theoretically that the proposed control strategy pushes the system away from the saturation state in finite time, and it ensures uniform ultimate boundedness result for the control error. The OFRAC strategy is applied to a virtual AM-AFM system, and the collected results clearly demonstrate that it presents superior imaging performance for high-speed scanning tasks.

Automatic tuning of PI controller for atomic force microscope based on relay with hysteresis

An atomic force microscope (AFM) usually employs proportional-integral (PI) control strategy to sustain a constant cantilever deflection. However, it is well known that the tuning of PI parameters is a tedious and complicated procedure, especially for those unfamiliar with control theory. In this paper, we employ and implement relay controller to automate the tuning procedure for contact-mode AFM PI controller during different scanning speed operations based on relay with hysteresis. Experimental results show that this approach offers system with satisfactory step response with typical settling time of about 2 ms. Moreover, better sample topography image can be obtained after auto-tuning the control gains during different scanning speed.

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.

Image-based hysteresis modeling and compensation for piezo-scanner utilized in AFM

As an important component of Atomic Force Microscope (AFM), piezo-scanner exhibits some undesired nonlinear characteristics, among which the inherent hysteresis largely decreases the scanning rate and resolution of AFM. To alleviate this problem, an image-based approach is proposed in this paper to model and then compensate for the hysteresis behavior of the piezo-scanner. Specifically, some scanning images over calibration grating are utilized to identify the parameters of the classical Preisach model (CPM) of hysteresis. Based on the obtained model, an inversion-based technique is adopted to design a compensator for the hysteresis of piezo-scanner. The proposed algorithm presents such advantages of low cost and little complexity since no nano-sensor is required to collect identification data. Some simulation results are included to demonstrate the performance of the proposed strategy.

Output feedback robust adaptive controller design for dynamic atomic force microscopy

This paper analyzes the dynamics of amplitude modulation atomic force microscope (AM-AFM) which is the mostly employed mode in current AFMs. A reduced model is proposed to approximate the function of tip-sample separation to oscillation amplitude. Considering the fact that the model parameters vary with different combinations of piezo-scanner and cantilever as well as the measured sample, a robust adaptive controller is designed to reduce the system regulation error. Specifically, by using the K-filter, an observer is designed firstly for this output feedback problem. Based on this observer, we design a robust adaptive controller consisting of two parts: an adaptive component is used to deal with the unknown parameters, while the model uncertainty and system disturbance are accounted for by a robust control part. With the aid of Lyapunov technique, the stability of this control method is guaranteed and GUUB result is obtained. Additionally, the attractive region is analyzed particularly in the case of measurement saturation which usually occurs in dynamic AFM mode. To verify its effectiveness, some simulation results are included to show the performance of the proposed control strategy.

Field programmable gate array (FPGA) based embedded system design for AFM real-time control

This report describes the realization of an embedded hardware system designed to perform fast control for an atomic force microscope (AFM). Traditional implementation of control algorithms for AFMs, either PC-based or DSP-based, does not meet the high-speed scanning requirement. Considering the capability of parallel computing, FPGA is employed to achieve real-time control for an AFM equipment. Specifically, in the designed embedded system, the hardware includes several key components of signal acquisition, signal conversion, data communication as well as the FPGA-based control law implementation. Besides higher control frequency, the designed FPGA-based embedded system provides a general platform for different advanced control strategies, on which a variety of control algorithms can be implemented and tested conveniently by replacing the codes in the software rather than changing hardware structure, due to the merit that FPGA can integrate internal CPU and it has a large number of logic cells and soft-cores. The widely utilized proportional-integral- derivative (PID) algorithm is chosen as an example to demonstrate the implementation of a controller by using powerful hardware description tools.