Improvement of accuracy and speed of a commercial AFM using Positive Position Feedback control

The atomic force microscope (AFM) is a device capable of generating topographic images of sample surfaces with extremely high resolutions down to the atomic level. It is also being used in applications that involve manipulation of matter at a nanoscale. Early AFMs were operated in open loop. As a result, they were susceptible to piezoelectric creep, thermal drift, hysteresis nonlinearity and scan-induced vibration. These effects tend to distort the generated image. The distortions are often minimized by limiting the scanning speed and range of the AFMs. Recently a new generation of AFMs has emerged that utilizes position sensors to measure displacements of the scanner in three dimensions. These AFMs are equipped with feedback loops that work to minimize the adverse effects of hysteresis, piezoelectric creep and thermal drift on the obtained image using standard PI controllers. These feedback controllers are often not designed to deal with the highly resonant nature of an AFM's scanner, nor with the cross-coupling between various axes. In this paper we illustrate the drastic improvement in accuracy and imaging speed that can be obtained by proper design of a feedback controller. Such controllers can be incorporated into most modern AFMs with minimal effort since they can be implemented in software with the existing hardware

Design and implementation of high-bandwidth, high-resolution imaging in atomic force microscopy

Video-rate imaging with subnanometer resolution without compromising on the scan range has been a long-awaited goal in Atomic Force Microscopy (AFM). The past decade saw significant advances in hardware used in atomic force microscopes, which further enable the feasibility of high-speed Atomic Force Microscopy. Control design in AFMs plays a vital role in realizing the achievable limits of the device hardware. Almost all AFMs in use today use Proportional-Integral-Derivative(PID) control designs, which can be majorly improved upon for performance and robustness. We address the problem of AFM control design through a systems approach to design model-based control laws that can give major improvements in the performance and robustness of AFM imaging. First, we propose a cascaded control design approach to tapping mode imaging, which is the most common mode of AFM imaging. The proposed approach utilizes the vertical positioning sensor in addition to the cantilever deflection sensor in the feedback loop. The control design problem is broken down into that of an inner control loop and an outer control loop. We show that by appropriate control design, unwanted effects arising out of model uncertainties and nonlinearities of the vertical positioning system are eliminated. Experimental implementation of the proposed control design shows improved imaging quality at up to 30% higher speeds. Secondly, we address a fundamental limitation in tapping mode imaging by proposing a novel transform-based imaging mode to achieve an order of magnitude improvement in AFM imaging bandwidth. We introduce a real-time transform that effects a frequency shift of a given signal. We combine model-based reference generation along with the real-time transform. The proposed method is shown to have linear dynamical characteristics, making it conducive for model-based control designs, thus paving the way for achieving superior performance and robustness in imaging

Performance-driven control of nano-motion systems

The performance of high-precision mechatronic systems is subject to ever increasing demands regarding speed and accuracy. To meet these demands, new actuator drivers, sensor signal processing and control algorithms have to be derived. The state-of-the-art scientific developments in these research directions can significantly improve the performance of high-precision systems. However, translation of the scientific developments to usable technology is often non-trivial. To improve the performance of high-precision systems and to bridge the gap between science and technology, a performance-driven control approach has been developed. First, the main performance limiting factor (PLF) is identified. Then, a model-based compensation method is developed for the identified PLF. Experimental validation shows the performance improvement and reveals the next PLF to which the same procedure is applied. The compensation method can relate to the actuator driver, the sensor system or the control algorithm. In this thesis, the focus is on nano-motion systems that are driven by piezo actuators and/or use encoder sensors. Nano-motion systems are defined as the class of systems that require velocities ranging from nanometers per second to millimeters per second with a (sub)nanometer resolution. The main PLFs of such systems are the actuator driver, hysteresis, stick-slip effects, repetitive disturbances, coupling between degrees-of-freedom (DOFs), geometric nonlinearities and quantization errors. The developed approach is applied to three illustrative experimental cases that exhibit the above mentioned PLFs. The cases include a nano-motion stage driven by a walking piezo actuator, a metrological AFM and an encoder system. The contributions of this thesis relate to modeling, actuation driver development, control synthesis and encoder sensor signal processing. In particular, dynamic models are derived of the bimorph piezo legs of the walking piezo actuator and of the nano-motion stage with the walking piezo actuator containing the switching actuation principle, stick-slip effects and contact dynamics. Subsequently, a model-based optimization is performed to obtain optimal drive waveforms for a constant stage velocity. Both the walking piezo actuator and the AFM case exhibit repetitive disturbances with a non-constant period-time, for which dedicated repetitive control methods are developed. Furthermore, control algorithms have been developed to cope with the present coupling between and hysteresis in the different axes of the AFM. Finally, sensor signal processing algorithms have been developed to cope with the quantization effects and encoder imperfections in optical incremental encoders. The application of the performance-driven control approach to the different cases shows that the different identified PLFs can be successfully modeled and compensated for. The experiments show that the performance-driven control approach can largely improve the performance of nano-motion systems with piezo actuators and/or encoder sensors