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

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

PKM mechatronic clamping adaptive device

This study proposes a novel adaptive fixturing device based on active clamping systems for smart micropositioning of thin-walled precision parts. The modular architecture and the structure flexibility make the system suitable for various industrial applications. The proposed device is realized as a Parallel Kinematic Machine (PKM), opportunely sensorized and controlled, able to perform automatic error-free workpiece clamping procedures, drastically reducing the overall fixturing set-up time. The paper describes the kinematics and dynamics of this mechatronic system. A first campaign of experimental trails has been carried out on the prototype, obtaining promising results

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

An analytical approach to integral resonant control of second-order systems

Peer reviewedPostprin

Model reference control for ultra-high precision positioning systems

Due to the increasing demands of high-density semiconductors, molecular biology, optoelectronics, and MEMS/NEMS in the past decades, control of ultra-high precision positioning using piezoelectricity has become an important area because of its high displacement resolution, wide bandwidth, low power consumption, and potential low cost. However, the relatively small displacement range limits its application. This work proposed a practical ultra-high precision piezoelectric positioning system with a complementary high displacement range actuation technology. Solenoids are low cost, high speed electromagnetic actuators which are commonly used in on-off mode only because of the inherent high nonlinear force-stroke characteristics and unipolar forces (push/pull) generated by the magnetic fields. In this work, an integrated positioning system based on a monolithic piezoelectric positioner and a set of push-pull dual solenoid actuators is designed for high speed and high precision positioning applications. The overall resolution can be sub-nanometer while the moving range is in millimeters, a three order of magnitude increase from using piezoelectric positioner alone. The dynamic models of the dual solenoid actuator and piezoelectric nanopositioner are derived. The main challenge of designing such positioning systems is to maintain the accuracy and stability in the presence of un-modeled dynamics, plant variations, and parasitic nonlinearities, specifically in this work, the friction and forcestroke nonlinearities of the dual solenoid actuator, and the friction, hysteresis and coupling effects of piezoelectric actuator, which are impossible to be modeled accurately and even time-varying. A model reference design approach is presented to attenuate linear as well as nonlinear uncertainties, with a fixed order controller augmenting a reference model that embeds the nominal dynamics of the plant. To improve transient characteristics, a Variable Model Reference Zero Vibration (VMRZV) control is also proposed to stabilize the system and attenuate the adverse effect of parasitic nonlinearities of micro-/nano- positioning actuators and command-induced vibrations. The speed of the ultra-high precision system with VMRZV control can also be quantitatively adjusted by systematically varying the reference model. This novel control method improves the robustness and performance significantly. Preliminary experimental data on dual solenoid system confirm the feasibility of the proposed method

Observer techniques applied to the control of piezoelectric Microactuators.

International audienceWe present here the use of sensors, observers and self-sensing techniques to control piezoelectric actuators, particularly piezocantielevers. First, the feedback control with full measurements (all variables are measured) is presented. Because of the lack of convenient sensors for the microworld, nonfull measurements combined with observer techniques is proposed. Finally, the self-sensing principle, where the actuator is at the same time sensor, is applied and used for the feedback

Optimal integral force feedback and structured PI tracking control : application for objective lens positioner

Peer reviewedPostprin

Ultraprecise Controller for Piezoelectric Actuators Based on Deep Learning and Model Predictive Control

Piezoelectric actuators (PEA) are high-precision devices used in applications requiring micrometric displacements. However, PEAs present non-linearity phenomena that introduce drawbacks at high precision applications. One of these phenomena is hysteresis, which considerably reduces their performance. The introduction of appropriate control strategies may improve the accuracy of the PEAs. This paper presents a high precision control scheme to be used at PEAs based on the model-based predictive control (MPC) scheme. In this work, the model used to feed the MPC controller has been achieved by means of artificial neural networks (ANN). This approach simplifies the obtaining of the model, since the achievement of a precise mathematical model that reproduces the dynamics of the PEA is a complex task. The presented approach has been embedded over the dSPACE control platform and has been tested over a commercial PEA, supplied by Thorlabs, conducting experiments to demonstrate improvements of the MPC. In addition, the results of the MPC controller have been compared with a proportional-integral-derivative (PID) controller. The experimental results show that the MPC control strategy achieves higher accuracy at high precision PEA applications such as tracking periodic reference signals and sudden reference change