Smart Materials-Based Actuators at the Micro/Nano-Scale

The main motivations of using smart materials as fundamental in micro/ nanopositioning systems are presented in this chapter. It is shown that the design of classical (or macro) actuated systems cannot directly be used to design small ones, particularly those used for micro/nanopositioning. While in macro, many components are assembled to form the actuated systems, in micro one attempts to reduce the number of elements in order to ensure some resolution and accuracy of positioning and in order to make easy their fabrication. Smart and active materials are therefore seen as the principal and essential component in microsystems and systems working at the micro/nano-scale. Their advantages are detailed in the chapter and some of the behaviors (hysteresis and creep) that are often encountered are explained. A particular attention is given to piezoelectric materials since nine chapters of the book treat them.

A magnetic hybrid material consisting of iron oxide nanoparticles (4 nm) embedded in a polymer matrix of Na-CMC was synthesized. The synthesis was done from a chemical treatment on a precursor hybrid material previously synthesized. The structure, morphology, and magnetic properties for this magnetic hybrid material were studied by X-ray diffraction, IR spectroscopy, transmission electron microscopy, and magnetometry. Additionally, the dynamic response was analyzed in order to probe the feasibility to use this magnetic hybrid material as a bending-type actuator. The experimental results show that the responses of the deflection have a linear trend over a reasonable range, suggesting that the magnetic hybrid material can be used as bending-type actuators in small mechanical systems and devices. First simulations have also been done considering the two components of the magnetic hybrid material: the oxide iron nanoparticles and Na-CMC. The displacement response takes in account the viscoelastic properties of the polymeric matrix and the magnetization of the nanoparticles.

This chapter presents the characterization, modeling, and robust control of a nonlinear and oscillating 2-degrees of freedom (2-dof) piezoelectric cantilevered actuator. The actuator possesses a high resolution and a high bandwidth of the actuator, however, it is typified by a hysteresis and creep nonlinearities, a badly damped vibration and a strong coupling between the two axes. Based on the quadrilateral approach, a simple model which can account efficiently all these properties is proposed. Indeed, the model is linear followed by well-defined uncertainties and perturbations. In order to ensure certain performances, a robust standard H _∞ control technique is used to synthesize controllers for the 2-dof actuator. The experimental results confirm the efficiency of the proposed approach of modeling and control design.

Precise position control on the nanometer and subnanometer scale, referred to as nanopositioning, is a key enabler for nanoscale science and engineering. In nanopositioning, feedback control is essential to meet the stringent requirements on accuracy, stability, and repeatability in the presence of model uncertainties and environmental disturbances. In this chapter, we review a new hybrid control approach to nanopositioning which is based on the combination of a continuous-time control law with impulsive modifications of the controller states. By using impulsive control, the limitations of conventional linear controllers can be overcome, such as the inherent trade-off between closed-loop bandwidth and resolution. We review the related literature, present an in-depth analysis of the stability and performance characteristics of impulsive control, and verify the theoretical conclusions experimentally using a custom-built atomic force microscope.

This chapter presents the modeling and the control of piezoelectric-based microactuators. Typified by uncertainties of models, we propose to use intervals to bound the uncertain parameters. These uncertainties are particularly due to the difficulties to perform precise identification and to the high sensivity of the systems at the micro/nanoscale. In order to account the models uncertainties, we propose therefore to combine interval tools and classical control theory to derive robust controllers. Experimental results confirm the predicted theory and demonstrate the efficiency of the proposed method.

This chapter deals with the state estimation with noise rejection in a piezoelectric cantilevered actuator and its state-feedback control. The noises which come from the sensor used, strain gage, are important and should be filtered. For that, we employ the classical Kalman filtering for their rejection and for the state estimation and we apply afterwards a state-feedback control with integral action to improve the general performances of the actuator. However, as the actuator exhibits hysteresis nonlinearity, we propose first its linearization thanks to a feedforward control before application of the above filtering and feedback control. The experimental results confirm the efficiency of the approach and demonstrate the interest of the method for precise positioning such as in micropositioning applications.

This chapter presents a new approach to hysteresis modeling and compensation of piezoelectric actuators by resorting to an intelligent model. A least squares support vector machine (LSSVM)-based hysteresis model is developed and used for the purposes of both hysteresis characterization and compensation. By this way, the hysteresis inverse is not needed in the feedforward hysteresis compensator since only the hysteresis model is used. The effectiveness of the presented approach is validated by experimental studies on a piezoactuated system. Experimental results confirm that this approach is superior to Bouc–Wen model in terms of both hysteresis modeling and compensation.

Piezomicropositioning actuators exhibit strong rate-dependent hysteresis nonlinearities that affect the accuracy of these micropositioning systems in open-loop system and may even lead to system instability of the closed-loop control system. Compensation of rate-dependent hysteresis effects using inverse rate-independent hysteresis models may yield high compensation error at high-excitation frequencies since these hysteresis effects increase as the excitation frequency of the input voltage increases. The inverse rate-dependent Prandtl–Ishlinskii model is utilized for compensation of the rate-dependent hysteresis nonlinearities in a piezomicropositioning stage. The exact inversion of the rate-dependent model is on hold under the condition that the distances between the thresholds do not decrease in time. The inverse of the rate-dependent model is applied as a feedforward compensator to compensate for the rate-dependent hysteresis nonlinearities of a piezomicropositioning actuator at different excitation frequencies between 0.1 and 50 Hz. The results show that the inverse compensator suppresses the hysteresis percent and the maximum positioning error in the output displacement of the piezomicropositioning actuator at different excitation frequencies, respectively.

In this chapter, the control without sensors, also called feedforward control, of piezoelectric actuators is proposed. Typified by hysteresis and creep nonlinearities and by badly damped vibration, the design of the controller (compensator) is based on precise models and on the inversion of the latter. For that, the hysteresis is first modeled and compensated by using the Prandtl–Ishlinskii technique. Then, the creep is treated. Finally, the badly damped vibration is modeled and controlled. Experimental results along the chapter demonstrate the efficiency of the approach.

This chapter presents the fabrication and characterization of piezoresistive force sensors based on helical nanobelts. The three-dimensional helical nanobelts are self-formed from 27-nm-thick n-type InGaAs/GaAs bilayers using rolled-up techniques and assembled onto electrodes on a micropipette using nanorobotic manipulation. Patterned gold electrodes were fabricated using thermal evaporation or fountain-pen-based gold nanoink deposition. Nanomanipulation inside a scanning electron microscope was conducted to locate small metal pads of helical nanobelts to be connected to the fabricated pipette-type electrodes. Gold nanoink was deposited under optical micrograph using the fountain-pen method. Nanomanipulation inside a scanning electron microscope using a calibrated atomic force microscope cantilever was conducted to calibrate the assembled force sensors, and the values were compared with finite-element-method simulation results. With their strong piezoresistive response, low stiffness, large-displacement capability, and good fatigue resistance, these force sensors are well suited to function as sensing elements for high-resolution and large-range electromechanical sensors.

Sperm analysis and manipulation play a significant role in biology research and reproductive medicine (assisted reproductive technologies). This chapter reviews computer vision-based sperm tracking methods, sperm analysis techniques, and automated sperm manipulation. Based on computer vision tracking of sperm head and sperm tail, sperm motility can be quantified by calculating the sperm’s straight line velocity, curvilinear velocity, moving path linearity, and the sperm tail beating amplitude. Conventional computer-assisted sperm analysis (CASA) systems are capable of performing some of these tasks. Recent progress in this field provides additional, enhanced capabilities to biologists and clinical embryologists. This chapter also introduces recent progress in automating sperm manipulation procedures, including sperm immobilization, aspiration, and positioning inside a micropipette.