Modeling and Control of Piezoactive Micro and Nano Systems

Piezoelectrically-driven (piezoactive) systems such as nanopositioning platforms, scanning probe microscopes, and nanomechanical cantilever probes are advantageous devices enabling molecular-level imaging, manipulation, and characterization in disciplines ranging from materials science to physics and biology. Such emerging applications require precise modeling, control and manipulation of objects, components and subsystems ranging in sizes from few nanometers to micrometers. This dissertation presents a comprehensive modeling and control framework for piezoactive micro and nano systems utilized in various applications. The development of a precise memory-based hysteresis model for feedforward tracking as well as a Lyapunov-based robust-adaptive controller for feedback tracking control of nanopositioning stages are presented first. Although hysteresis is the most degrading factor in feedforward control, it can be effectively compensated through a robust feedback control design. Moreover, an adaptive controller can enhance the performance of closed-loop system that suffers from parametric uncertainties at high-frequency operations. Comparisons with the widely-used PID controller demonstrate the effectiveness of the proposed controller in tracking of high-frequency trajectories. The proposed controller is then implemented in a laser-free Atomic Force Microscopy (AFM) setup for high-speed and low-cost imaging of surfaces with micrometer and nanometer scale variations. It is demonstrated that the developed AFM is able to produce high-quality images at scanning frequencies up to 30 Hz, where a PID controller is unable to present acceptable results. To improve the control performance of piezoactive nanopositioning stages in tracking of time-varying trajectories with frequent stepped discontinuities, which is a common problem in SPM systems, a supervisory switching controller is designed and integrated with the proposed robust adaptive controller. The controller switches between two control modes, one mode tuned for stepped trajectory tracking and the other one tuned for continuous trajectory tracking. Switching conditions and compatibility conditions of the control inputs in switching instances are derived and analyzed. Experimental implementation of the proposed switching controller indicates significant improvements of control performance in tracking of time-varying discontinuous trajectories for which single-mode controllers yield undesirable results. Distributed-parameters modeling and control of rod-type solid-state actuators are then studied to enable accurate tracking control of piezoactive positioning systems in a wide frequency range including several resonant frequencies of system. Using the extended Hamilton\u27s principle, system partial differential equation of motion and its boundary conditions are derived. Standard vibration analysis techniques are utilized to formulate the truncated finite-mode state-space representation of the system. A new state-space controller is then proposed for asymptotic output tracking control of system. Integration of an optimal state-observer and a Lyapunov-based robust controller are presented and discussed to improve the practicability of the proposed framework. Simulation results demonstrate that distributed-parameters modeling and control is inevitable if ultra-high bandwidth tracking is desired. The last part of the dissertation, discusses new developments in modeling and system identification of piezoelectrically-driven Active Probes as advantageous nanomechanical cantilevers in various applications including tapping mode AFM and biomass sensors. Due to the discontinuous cross-section of Active Probes, a general framework is developed and presented for multiple-mode vibration analysis of system. Application in the precise pico-gram scale mass detection is then presented using frequency-shift method. This approach can benefit the characterization of DNA solutions or other biological species for medical applications

MICROCANTILEVER-BASED FORCE SENSING, CONTROL AND IMAGING

This dissertation presents a distributed-parameters base modeling framework for microcantilever (MC)-based force sensing and control with applications to nanomanipulation and imaging. Due to the widespread applications of MCs in nanoscale force sensing or atomic force microscopy with nano-Newton to pico-Newton force measurement requirements, precise modeling of the involved MCs is essential. Along this line, a distributed-parameters modeling framework is proposed which is followed by a modified robust controller with perturbation estimation to target the problem of delay in nanoscale imaging and manipulation. It is shown that the proposed nonlinear model-based controller can stabilize such nanomanipulation process in a very short time compared to available conventional methods. Such modeling and control development could pave the pathway towards MC-based manipulation and positioning. The first application of the MC-based (a piezoresistive MC) force sensors in this dissertation includes MC-based mass sensing with applications to biological species detection. MC-based sensing has recently attracted extensive interest in many chemical and biological applications due to its sensitivity, extreme applicability and low cost. By measuring the stiffness of MCs experimentally, the effect of adsorption of target molecules can be quantified. To measure MC\u27s stiffness, an in-house nanoscale force sensing setup is designed and fabricated which utilizes a piezoresistive MC to measure the force acting on the MC\u27s tip with nano-Newton resolution. In the second application, the proposed MC-based force sensor is utilized to achieve a fast-scan laser-free Atomic Force Microscopy (AFM). Tracking control of piezoelectric actuators in various applications including scanning probe microscopes is limited by sudden step discontinuities within time-varying continuous trajectories. For this, a switching control strategy is proposed for effective tracking of such discontinuous trajectories. A new spiral path planning is also proposed here which improves scanning rate of the AFM. Implementation of the proposed modeling and controller in a laser-free AFM setup yields high quality image of surfaces with stepped topographies at frequencies up to 30 Hz. As the last application of the MC-based force sensors, a nanomanipulator named here MM3A® is utilized for nanomanipulation purposes. The area of control and manipulation at the nanoscale has recently received widespread attention in different technologies such as fabricating electronic chipsets, testing and assembly of MEMS and NEMS, micro-injection and manipulation of chromosomes and genes. To overcome the lack of position sensor on this particular manipulator, a fused vision force feedback robust controller is proposed. The effects of utilization of the image and force feedbacks are individually discussed and analyzed for use in the developed fused vision force feedback control framework in order to achieve ultra precise positioning and optimal performance

Workshop on "Control issues in the micro / nano - world".

International audienceDuring the last decade, the need of systems with micro/nanometers accuracy and fast dynamics has been growing rapidly. Such systems occur in applications including 1) micromanipulation of biological cells, 2) micrassembly of MEMS/MOEMS, 3) micro/nanosensors for environmental monitoring, 4) nanometer resolution imaging and metrology (AFM and SEM). The scale and requirement of such systems present a number of challenges to the control system design that will be addressed in this workshop. Working in the micro/nano-world involves displacements from nanometers to tens of microns. Because of this precision requirement, environmental conditions such as temperature, humidity, vibration, could generate noise and disturbance that are in the same range as the displacements of interest. The so-called smart materials, e.g., piezoceramics, magnetostrictive, shape memory, electroactive polymer, have been used for actuation or sensing in the micro/nano-world. They allow high resolution positioning as compared to hinges based systems. However, these materials exhibit hysteresis nonlinearity, and in the case of piezoelectric materials, drifts (called creep) in response to constant inputs In the case of oscillating micro/nano-structures (cantilever, tube), these nonlinearities and vibrations strongly decrease their performances. Many MEMS and NEMS applications involve gripping, feeding, or sorting, operations, where sensor feedback is necessary for their execution. Sensors that are readily available, e.g., interferometer, triangulation laser, and machine vision, are bulky and expensive. Sensors that are compact in size and convenient for packaging, e.g., strain gage, piezoceramic charge sensor, etc., have limited performance or robustness. To account for these difficulties, new control oriented techniques are emerging, such as[d the combination of two or more ‘packageable' sensors , the use of feedforward control technique which does not require sensors, and the use of robust controllers which account the sensor characteristics. The aim of this workshop is to provide a forum for specialists to present and overview the different approaches of control system design for the micro/nano-world and to initiate collaborations and joint projects

Improvement in the Imaging Performance of Atomic Force Microscopy: A Survey

Nanotechnology is the branch of science which deals with the manipulation of matters at an extremely high resolution down to the atomic level. In recent years, atomic force microscopy (AFM) has proven to be extremely versatile as an investigative tool in this field. The imaging performance of AFMs is hindered by: 1) the complex behavior of piezo materials, such as vibrations due to the lightly damped low-frequency resonant modes, inherent hysteresis, and creep nonlinearities; 2) the cross-coupling effect caused by the piezoelectric tube scanner (PTS); 3) the limited bandwidth of the probe; 4) the limitations of the conventional raster scanning method using a triangular reference signal; 5) the limited bandwidth of the proportional-integral controllers used in AFMs; 6) the offset, noise, and limited sensitivity of position sensors and photodetectors; and 7) the limited sampling rate of the AFM's measurement unit. Due to these limitations, an AFM has a high spatial but low temporal resolution, i.e., its imaging is slow, e.g., an image frame of a living cell takes up to 120 s, which means that rapid biological processes that occur in seconds cannot be studied using commercially available AFMs. There is a need to perform fast scans using an AFM with nanoscale accuracy. This paper presents a survey of the literature, presents an overview of a few emerging innovative solutions in AFM imaging, and proposes future research directions.This work was supported in part by the Australian Research Council (ARC) under Grant FL11010002 and Grant DP160101121 and the UNSW Canberra under a Rector's Visiting Fellowshi

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

Microrobots for wafer scale microfactory: design fabrication integration and control.

Future assembly technologies will involve higher automation levels, in order to satisfy increased micro scale or nano scale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to micro-electronics and MEMS industries, but less so in nanotechnology. With the bloom of nanotechnology ever since the 1990s, newly designed products with new materials, coatings and nanoparticles are gradually entering everyone’s life, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than with top-down robotic assembly. This is due to considerations of volume handling of large quantities of components, and the high cost associated to top-down manipulation with the required precision. However, the bottom-up manufacturing methods have certain limitations, such as components need to have pre-define shapes and surface coatings, and the number of assembly components is limited to very few. For example, in the case of self-assembly of nano-cubes with origami design, post-assembly manipulation of cubes in large quantities and cost-efficiency is still challenging. In this thesis, we envision a new paradigm for nano scale assembly, realized with the help of a wafer-scale microfactory containing large numbers of MEMS microrobots. These robots will work together to enhance the throughput of the factory, while their cost will be reduced when compared to conventional nano positioners. To fulfill the microfactory vision, numerous challenges related to design, power, control and nanoscale task completion by these microrobots must be overcome. In this work, we study three types of microrobots for the microfactory: a world’s first laser-driven micrometer-size locomotor called ChevBot，a stationary millimeter-size robotic arm, called Solid Articulated Four Axes Microrobot (sAFAM), and a light-powered centimeter-size crawler microrobot called SolarPede. The ChevBot can perform autonomous navigation and positioning on a dry surface with the guidance of a laser beam. The sAFAM has been designed to perform nano positioning in four degrees of freedom, and nanoscale tasks such as indentation, and manipulation. And the SolarPede serves as a mobile workspace or transporter in the microfactory environment