Correct tuning of feedback gains is important for AFMs to cope with uncertainties of the system dynamics coming from a large range of different samples, cantilevers and scan parameters. For state of the art AFMs gains have to be adjusted manually by the operator. The typical operator such as biologist, physicist or material scientist may not have detailed knowledge about control engineering. In order to increase usability and acceptance an easy and intuitive approach is needed. The method presented in this paper is based on the commonly applied manual tuning strategy for AFM-imaging and copies the behavior of an experienced user. By spectral analysis ringing of the feedback loop is detected when feedback gains are increased beyond the stability margins. Increasing gains is stopped when an 1/f stop criteria is reached. The algorithm is successfully tested in simulation and practical AFM topography measurements with different cantilever - sample combinations, demonstrating that auto-tuning can be applied to achieve imaging performance close to ideal settings.

Fast steering mirrors (FMSs) are used in various applications like optical scanning of surfaces, feature detection or beam steering for optical communication systems. This paper introduces Lissajous scan trajectories to improve the tracking performance of a commercial FSM scanning system. The design of a dual tone (DT) feedback controller is presented that is tailored to this type of trajectory and the low-stiffness properties of electromagnetically actuated systems. It is shown that the controller can be used to eliminate periodic errors resulting from remaining cross-talk between the system axes. The DT controller significantly improves the tracking performance as compared to conventional wide bandwidth (WBW) control of the FSM. Applying the tailored controller with Lissajous trajectories reduces the RMS tracking error to 0.77%, as compared to more than 9.1% for the conventional raster scan with a WBW controller. The peak error is reduced from 16% for the raster scan to 1.1% for the Lissajous scan.

Robust feedback control with large parameter uncertainties in a high precision stage with large sample mass variation is presented. Instead of expressing the nominal plant and its uncertainty by parametric models, they are expressed using the identified frequency response data. The open loop transfer function is mapped onto a Nyquist plot, to assess robust stability. Next, the complementary sensitivity function is derived from this data to describe tracking performance, which is verified by experiments. The advantage is that the parameter estimation step is omitted, without compromising robust stability and performance.

Measuring properties at the nanometre scale such as topography, morphology and roughness within a production line becomes increasingly important for quality control and process monitoring tasks. In a production line, ground vibrations are transmitted to the sample and the inspection tool, corrupting nanoscale measurements by affecting the distance between inspection tool and sample. To enable nanometre scale measurements a mechanism is needed that keeps this distance constant. This paper describes the concept and experimental results of a metrology platform that tracks the sample for nanoscale inspection. The nano inspection tool is carried by the metrology platform and is artificially coupled to the movement of the sample by using a feedback controller. A one degree of freedom experimental setup was built for demonstrating tracking performance. The implemented closed loop control achieves disturbance rejection with a bandwidth of 410 Hz and reduces emulated on-site vibrations from ±500 nm down to ±9 nm, showing significant reduction of external vibrations.