Micky Rakotondrabe

Dynamic displacement self-sensing and robust control of cantilever piezoelectric actuators dedicated for microassembly

The main objective of this paper is the dynamic self-sensing of the motion of piezoelectric actuators. The proposed measurement technique is afterwards used for a closed-loop control. Aiming to obtain a self-sensing scheme that estimates the transient and steady-state modes of the displacement, we extend a previous static self-sensing scheme by adding a dynamic part. Analytical solutions are provided to compute the gains of this dynamic part. Afterwards, the proposed dynamic self-sensing result is used in a closed-loop control. The experimental results demonstrate the concept and evaluate the accuracy and the efficiency of the proposed technique for closed-loop applications.

Modeling, identification and feedforward control of multivariable hysteresis by combining Bouc-Wen equations and the inverse multiplicative structure

This paper deals with the modeling, identification and feedforward control of hysteresis found in multi-degrees of freedom (DOF) piezoelectric actuators. One main characteristic of the considered hysteresis behavior is the strong couplings. To express such multivariable hysteresis, we propose to extend the previous Bouc-Wen hysteresis monovariable model used for 1-DOF actuators. Then we propose to combine the resulting multivariable model with the inverse multiplicative structure in order to derive a multivariable compensator that suppresses the direct and the coupling hysteresis. Experimental tests on a piezotube scanner demonstrate the efficiency of the proposed approach.

Microfabricated PMN-PT on silicon cantilevers with improved static and dynamic piezoelectric actuation: Development, characterization and control

The paper reports a new composite bimorph Piezo-MEMS actuator based on the mono-crystalline and high piezoelectric coefficient material PMN-PT. The technology is based on the gold bonding of two bulk materials (PMN-PT and Silicon) followed by the Deep Reactive Ion Etching (DRIE) on the silicon side, leading to an optimized displacement actuator. The process requires an external re-polarization, yet the piezoelectric properties are conserved. The device is characterized then modeled and operated in a closed-loop control. The actuation capabilities results are compared to the ones of a classical PZT-ceramic actuator of equivalent size, demonstrating a 3 to 4 times net gain in terms of displacement range. The dynamics are improved by a factor of 2.5X for the same actuating range. The newly microfabricated actuator is also lighter and compatible with the silicon batch fabrication. Future applications include microrobotics, microassembly, cells and gene manipulation etc.

Dynamic force/position modeling of a one-DOF smart piezoelectric micro-finger with sensorized end-effector

In this paper, a generic microscale system is studied where a smart microsystem composed of an active based material actuator, sensorized structure and transformation system is studied. This problem is important at the microscale because it offers a force measurement of the applied force by the actuator to a flexible environment which enables to understand the interaction between the complete smart microsystem and the environment and to design and control the interaction between the system and the environment. A special case where a sensorized end-effector is fixed on the tip of a piezoelectric actuator is detailed. Integrating a sensorized end-effector influences the behavior of the smart microfinger and is not studied in recent works. The complete finger, which is called in this paper smart finger, consists of a piezoelectric actuator, an end-effector and a novel piezoresistive force sensor. A complete model is developed for generating both force and displacement at the fingers tip while interaction with a flexible environment. A nonlinear model of the piezoelectric actuator is considered and a complete model is developed taking into account the frequency dependent hysteresis of the piezoelectric actuator. The model of the hysteresis is based on the Bouc-Wen method which simplifies the parameter estimation. The complete dynamic force/position model of the finger is validated experimentally with small errors (less than 10%).

Introduction: Smart Materials as Essential Base for Actuators in Micro/Nanopositioning

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.

PMN-PT piezoelectric material and related applications in Silicon-integrated devices like microactuators and energy harvesters

Most of the actual MEMS (Micro-ElectroMechanical Systems) are Silicon capacitive devices. The reported research provides the means for approaching towards novel concepts combining silicon technology with piezoelectric materials into Piezo-MEMS systems. The presented technology is based on the bonding and patterning of bulk PMN-PT piezoelectric material on a Silicon wafer rather than sputtering thin piezoelectric films (a complementary method generally providing worse piezoelectric propertie)s. On the other hand bulk piezoelectric materials are more suited for micromanipulation actuators or energy harvesters. The advantage of PMN-PT piezoelectric material with respect to the classical PZT ceramics is presented in the context of the latest works. The technology and some results for actuation and energy harvesting are depicted in the paper.

Modeling and Robust H ∞ Control of a Nonlinear and Oscillating 2-dof Multimorph Cantilevered Piezoelectric Actuator

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.

Kalman Filtering and State-Feedback Control of a Nonlinear Piezoelectric Cantilevered Actuator

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.

Image schema based landing and navigation for rotorcraft MAV-S

To date, most autonomous micro air vehicles (MAV-s) operate in a controlled environment, where the location of and attitude of the aircraft are measured with an infrared (IR) tracking systems. If MAV-s are to ever exit the lab, their flight control needs to become autonomous and based on on-board image and attitude sensors. To address this need, several groups are developing monocular and binocular image based navigation systems. One of the challenges of these systems is the need for exact calibration in order to determine the vehicle’s position and attitude through the solution of an inverse problem. Body schemas are a biologically-inspired approach, emulating the plasticity of the animal brain, which allows it to learn non-linear mappings between the body configurations, i.e. its generalized coordinates and the resulting sensory outputs. The advantages of body schemas has long been recognized in the cognitive robotic literature and resulting studies on human-robot interactions based on artificial neural networks, however little effort has been made so far to develop avian-inspired flight control strategies utilizing body and image schemas.This paper presents a numerical experiment of controlling the trajectory of a miniature rotorcraft during landing maneuvers suing the notion of body and image schemas. More specifically, we demonstrate how trajectory planning can be executed in the image space using gradient-based maximum seeking algorithm of a pseudo-potential. It is demonstrated that a neural-gas type artificial neural network (ANN), trained through Hebbian-type learning algorithm, can be effective in learning a mapping between the rotorcraft’s position/attitude and the output of its vision sensors. Numerical simulation of the landing performance, including resulting landing errors are presented using an experimentally validated rotorcraft model.Copyright

Interval Modeling and Robust Feedback Control of Piezoelectric-Based Microactuators

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.