Gianluca Rizzello

Closed loop control of dielectric elastomer actuators based on self-sensing displacement feedback

This paper describes a sensorless control algorithm for a positioning system based on a dielectric elastomer actuator (DEA). The voltage applied to the membrane and the resulting current can be measured during the actuation and used to estimate its displacement, i.e., to perform self-sensing. The estimated displacement can be then used as a feedback signal for a position control algorithm, which results in a compact device capable of operating in closed loop control without the need for additional electromechanical or optical transducers. In this work, a circular DEA preloaded with a bi-stable spring is used as a case of study to validate the proposed control architecture. A comparison of the closed loop performance achieved using an accurate laser displacement sensor for feedback is also provided to better assess the performance limitations of the overall sensorless scheme.

Modeling, Identification, and Control of a Dielectric Electro-Active Polymer Positioning System

This paper deals with a positioning system based on a dielectric electro-active polymer membrane. The motion is generated by the deformation of the membrane caused by the electrostatic compressive force between two compliant electrodes applied on the surface of the polymer. This paper proposes a detailed electro-mechanical nonlinear model of the system, which is subsequently used to develop (in both time and frequency domains) various model-based feedback control laws. Accurate modeling is useful to compensate the nonlinear behavior of the actuator (caused by the material characteristics and geometry) and obtain PID controllers providing precise tracking of steps or sinusoidal reference signals. The various design strategies are compared on various experimental tests.

An electro-mechanically coupled model for the dynamic behavior of a dielectric electro-active polymer actuator

Dielectric electro-active polymer (DEAP) technology holds promise for enabling lightweight, energy efficient, and scalable actuators. The circular DEAP actuator configuration (also known as cone or diaphragm actuator) in particular shows potential in applications such as pumps, valves, micro-positioners and loudspeakers. For a quantitative prediction of the actuator behavior as well as for design optimization tasks, material models which can reproduce the coupled electromechanical behavior inherent to these actuators are necessary. This paper presents a non-linear viscoelastic model based on an electro-mechanical Ogden free energy expression for the DEAP. The DEAP model is coupled with a spring/mass system to study the dynamic performance of such a representative system from static behavior to 50 Hz. The system is identified and validated by several different experiments.

Modeling of the effects of the electrical dynamics on the electromechanical response of a DEAP circular actuator with a mass–spring load

This paper presents a modeling approach of an actuator system based on a dielectric electro-active polymer (DEAP) circular membrane mechanically loaded with a mass and a linear spring. The motion is generated by the deformation of the membrane caused by the electrostatic compressive force between two compliant electrodes applied on the surface of the polymer. A mass and a linear spring are used to pre-load the membrane, allowing stroke in the out-of-plane direction. The development of mathematical models which accurately describe the nonlinear coupling between electrical and mechanical dynamics is a fundamental step in order to design model-based, high-precision position control algorithms operating in high-frequency regimes (up to 150 Hz). The knowledge of the nonlinear electrical dynamics of the actuator driving circuit can be exploited during the control system design in order to achieve desirable features, such as higher modeling accuracy for high-frequency actuation, self-sensing or control energy minimization. This work proposes a physical model of the DEAP actuator system which couples both electrical and mechanical dynamics occurring during the actuation process. By means of numerous experiments, it is shown that the model can be used to predict both actuator current and displacement, and therefore to increase the overall displacement prediction accuracy with respect to actuator models which neglect electrical behavior.

A Self-Sensing Approach for Dielectric Elastomer Actuators Based on Online Estimation Algorithms

This paper develops a position self-sensing approach for a motion actuator based on a dielectric elastomer membrane. The proposed method uses voltage and current measurements to estimate the electrical resistance and capacitance online by means of a high-frequency low-amplitude voltage component injected in the actuation signal. The actual deformation is subsequently reconstructed using a model-based estimate of the electrical parameters implemented on a field programmable gate array platform (FPGA) with a sampling frequency of 20 kHz. The main peculiarity of the approach is the use of recursive identification and filtering algorithms that avoid the need of charge measurements. The self-sensing algorithm is extensively validated on a precision linear-motion actuator, which uses a nonlinear biasing system to obtain large actuation strokes.

Robust Position Control of Dielectric Elastomer Actuators Based on LMI Optimization

This paper develops a model-based control strategy for a bistable positioning system based on a dielectric elastomer. The motion is generated by the electrostatic compressive force between two compliant electrodes applied on the surface of the elastomer. The membrane is connected to a bistable spring that acts as a biasing element and significantly extends the possible stroke. Such a design choice, however, makes the system strongly nonlinear and unstable in open-loop. Starting from the extension of a dynamic model developed for a simpler version of the actuator, this paper proposes a strategy based on robust control design tools for linear parameter-varying systems. The approach guarantees both stability and worst case performance in the whole operating range of the system. Both simulations and experiments are used to assess the advantages of the proposed design method.

Self-sensing in dielectric electro-active polymer actuator using linear-in-parametes online estimation

This paper presents a self-sensing methodology for Dielectric ElectroActive Polymer actuators. The proposed approach is based on using DEAP voltage and current to estimate electrical resistance and capacitance, and using the latter to reconstruct the actuator deformation. For the estimation of the electrical parameters, the performance of two standard linear regression algorithms are compared, i.e. standard Least Mean Squares (LMS) and Recursive Least Squares (RLS). Some filtering techniques are also suggested in order to improve the quality of the estimation. The full algorithm is first illustrated in detail and then validated on an experimental actuator prototype, consisting in a DEAP membrane combined with a bi-stable biasing element which enables large actuation stroke.

Robust Control of High-Speed Synchronous Reluctance Machines

High-speed regimes allow to increase the power density of electrical drives, which is a necessary characteristic in aeronautical applications. In such a context, together with the typical non-linearity of low speed drives, such as core saturation, phenomena related to high fundamental to sampling frequency ratios appear increasingly significant. This paper applies methodologies based on modern robust control to high-speed synchronous reluctance machines. The proposed method is based on a reformulation of the motor model as a linear parameter varying system. This allows transforming the current controller design in a multivariable optimization problem, which is solved with efficient numeric tools. Two digital controllers are developed, one designed in the continuous time domain and discretized for the implementation, and another directly designed in discrete time domain. Their performances are compared with standard decoupled current control using PI regulators. Both numerical simulations and experiments on a laboratory bench are presented.

Modeling and control of innovative smart materials and actuators: A tutorial

The need for mechatronic devices that are lightweight, less cumbersome and able to produce small, quick and precise movements or forces is ever increasing in many fields of engineering. Many recent design solutions are based on electrically, magnetically or thermally activated materials, often referred to as smart materials. This tutorial paper overviews the main properties and the resulting applications of two recently discovered smart materials, magnetic shape memory alloys (MSMAs) and electroactive polymers (EAPs), which have complementary characteristics and seem suitable to overcome some of the inherent limitations of other materials widely used in industrial applications, such as piezoelectric ceramics. As many other smart materials, MSMAs and EAPs exhibit nonlinear, hysteretic and time-varying behaviors, and therefore this tutorial discusses the main ways to model and effectively compensate these critical issues with advanced control strategies.

A smart experimental technique for the optimization of dielectric elastomer actuator (DEA) systems

In order to aid in moving dielectric elastomer actuator (DEA) technology from the laboratory into a commercial product DEA prototypes should be tested against a variety of loading conditions and eventually in the end user conditions. An experimental test setup to seamlessly perform mechanical characterization and loading of the DEA would be a great asset toward this end. Therefore, this work presents the design, control and systematic validation of a benchtop testing station for miniature silicon based circular DEAs. A versatile benchtop tester is able to characterize and apply programmable loading forces to the DEA while measuring actuator performance. The tester successfully applied mechanical loads to the DEA (including positive, constant and negative stiffness loads) simulating biasing systems via an electromagnetic linear motor operating in closed loop with a force/mechanical impedance control scheme. The tester expedites mechanical testing of the DEA by eliminating the need to build intricate pre-load mechanisms or use multiple testing jigs for characterizing the DEA response. The results show that proper mechanical loading of the DEA increases the overall electromechanical sensitivity of the system and thereby the actuator output. This approach to characterize and apply variable loading forces to DEAs in a single test system will enable faster realization of higher performance actuators.