Actuator Devices Research Articles

New perspectives in architecture through transformable structures: A simulation study

Structures enabling transformability of buildings, components and materials at different levels gain significance in view of a sustainable built environment. Such structures are capable of obtaining different shapes in response to varying functional, environmental or loading conditions. Certain limitations of classic tensegrity and scissor-like structures, applied so far in an architectural and engineering context, are attributed to a limited number of possible configurations and a big number of actuators required. In this context, rigid-bar linkages offer a promising alternative with regard to constructability, modularity, transformability and control components integration. In achieving improved flexibility and controllability with a reduced number of actuation devices, a kinematics principle has been previously proposed by the authors that involves the reduction of the system to an externally controlled one degree-of-freedom mechanism in a multistep transformation process. The paper presents application of the kinematics principle in two classes of a transformable spatial rigid-bar linkage structure. Investigation of the system kinematics was conducted using parametric associative design. The kinematics principle is applied on a torus-shaped spatial structural system composed of planar interconnected linkages. Alternative motion sequences of multiple transformation steps by the planar linkages can be implemented for the stepwise adjustment of the joints to their desired values. The actuators employed are positioned at the ground supports and are detached from the main structural body. Thus, minimum structural self-weight, simplicity and reduced energy consumption become possible. The transformation approaches using parametric associative design are exemplified based on a selected motion sequence pattern. The case study demonstrates the high degree of control flexibility and transformability of the system.

Efficient Secure Routing Mechanisms for the Low-Powered IoT Network: A Literature Review

The Wireless Sensor Network in the Internet of Things (WSN-IoT) has been flourishing as another global breakthrough over the past few years. The WSN-IoT is reforming the way we live today by spreading through all areas of life, including the dangerous demographic aging crisis and the subsequent decline of jobs. For a company to increase revenues and cost-effectiveness growth should be customer-centered and agile within an organization. WSN-IoT networks have simultaneously faced threats, such as sniffing, spoofing, and intruders. However, WSN-IoT networks are often made up of multiple embedded devices (sensors and actuators) with limited resources that are joined via various connections in a low-power and lossy manner. However, to our knowledge, no research has yet been conducted into the security methods. Recently, a Contiki operating system’s partial implementation of Routing Protocol for Low Power & Lossy Network RPL’s security mechanisms was published, allowing us to evaluate RPL’s security methods. This paper presents a critical analysis of security issues in the WSN-IoT and applications of WSN-IoT, along with network management details using machine learning. The paper gives insights into the Internet of Things in Low Power Networks (IoT-LPN) architecture, research challenges of the Internet of Things in Low Power Networks, network attacks in WSN-IoT infrastructures, and the significant WSN-IoT objectives that need to be accompanied by current WSN-IoT frameworks. Several applied WSN-IoT security mechanisms and recent contributions have been considered, and their boundaries have been stated to be a significant research area in the future. Moreover, various low-powered IoT protocols have been further discussed and evaluated, along with their limitations. Finally, a comparative analysis is performed to assess the proposed work’s performance. The study shows that the proposed work covers a wide range of factors, whereas the rest of the research in the literature is limited.

High wet-strength, durable composite film with nacre-like structure for moisture-driven actuators

As an emerging two-dimensional nanomaterial, Ti3C2TX MXene exhibits promising applications in the fields of energy, electromagnetic shielding, sensors and actuators. However, the structural instability and vulnerability to oxidation of MXene limit its application in moisture self-driven actuator. In this work, a composite film of moisture actuator with a lamellar structure inspired by pearl was reported. The composite film consists of tannic acid-modified Mxene and bacterial cellulose (BC). The synergistic interaction between TA and MXene imparts MXene with toughness and oxidation resistance, whereas the introduction of high wet/dry strength BC imparts the composite film with high tensile strength (243.5 MPa for dry strength and 173.4 MPa for wet strength) and high fracture strain (7.4 %). In addition, the actuator is highly moisture sensitive with fast response (2.48 s) and high cycling stability (more than 100 cycles). The results provide a strategy for the development of moisture-driven soft actuators, and reveal the great promise of this moisture actuator for applications in soft bionic robots and flexible arms, solving the current shortcomings of poor durability and low strength of MXene-based actuators, establishing the foundation for a wider application of moisture actuator devices.

Electromechanical response of group-IV monochalcogenide monolayers

The electromechanical response of the group-IV monochalcogenide monolayers upon charge injection was investigated for applications in actuator devices and artificial muscles.

Stress-strain magnetoactive propulsion system

It is possible to create deformations in magnetically active polymeric materials by applying magnetic fields to them. This work develops a symmetrical design scheme of the device, in which the drive and control are carried out by two actuators located on opposite sides. The symmetric scheme with control from two sides allows transporting objects (cargo) in mutually opposite directions (forward and backward). It is proposed to use a magnetically active gel together with a magnetically active elastomer as magnetically active materials. The resulting force effect in the device actuator is produced by interaction of magnetic fields of electromagnets with magnetic fields of permanent magnets. Expressions for obtaining alternating magnetic fields which create conditions for generating alternating magnetic forces in the actuator of the device are given. A prototype design with a controller control device in which signals are generated for an optimum current pulse generator with adjustable duty cycle and duration is presented.

Multifunctional rotational active valve for flow control in paper-based microfluidic devices

In paper-based microfluidics, the development of a robust and multi-role valve mechanism is important for flow control to perform multistep biochemical assays. The previous valve designs were complex, limited in their operational capabilities to simply ON/OFF functionality, required complex circuitry and auxiliary devices for valve actuation, or were unfit for friendly user operation. Herein, we present a multifunctional, simple, robust and cost effective rotational active valve (RAV) for paper-based microfluidics devices. In addition to ON/OFF, it achieves variable flow velocity by varying the contact area of RAV channel, by varying the RAV channel length, or by changing the RAV channel width. The functionality was demonstrated in paper-based microfluidic devices for sequential delivery with intermixing, multi-reagent valve regulation with washing step, and fluid distribution to multiple delivery zones. Finally, we conducted a multistep biochemical assay for the detection of total protein, uric acid and albumin protein in human serum at various concentration (dilution ranges from 40% to 100%) using RAV. We believe that our RAV can solve complex biochemical assays in paper-based devices with potential to be commercialized due to its cost-effectiveness, easy fabrication and robust nature of flow control enabling to achieve a viable point-of-care diagnostic platform.

Identification of flow structures in a closed chamber in the presence of a needle plasma actuator

This study deals with the experimental characterization of the induced flow dynamics by a disk-needle-type plasma actuator driven by a sinusoidal generator and located in a rectangular cross-section burner. Flow characterization was performed using different plasma actuation conditions and standoff distances. Experiments were conducted under non-reactive flow conditions. Electrical characterization was carried out. Airflow behavior was also analyzed using smoke flow visualization. Smoke flow visualization showed the dynamic behavior of the plasma-induced flow. Post-processing of high-quality images was performed by using Proper Orthogonal Decomposition (POD) technique to recognize the dominant flow vortexes and coherent structures. This could support the design of plasma actuation devices in real combustors and be useful for the implementation of numerical models. Moreover, it has been concluded that flow dynamics can be controlled by a variation of the plasma power or the gap distance between two electrodes. Laser Droplet Velocimetry (LDV) was used to investigate the distribution of flow velocities and turbulent kinetic energy (TKE) at different plasma power values of the sinusoidal alternating current generator and standoff distances. From POD and LDV analyses, it has been observed that there is quite a linear relation between the POD energy of the first mode and the maximum TKE. The POD method could be used to identify motions in the flow field carrying the most TKE. TKE peaks are present in the area with the most energetic flow structures, as identified by the POD.

Prototyping and Experimental Investigation of Digital Hydraulically Driven Knee Exoskeleton

Digital hydraulic drives are known for their superior efficiency, power density, and robustness. Such advantages make them an attractive alternative (to electric drives) for actuation of exoskeleton devices. This work presents development of a prototype for such a digital hydraulically driven knee exoskeleton and its experimental testing. The device uses two miniature hydraulic cylinders and a novel mechanism to translate the linear motion to rotary motion. The device is controlled via a passive control method in the stance phase and a simplified model predictive control method in the swing phase. In this work, the design of the exoskeleton device is optimized with respect to compactness and weight. Next, the features of the design are further refined to ensure that the device is able to support the operational loads. This design is then realized into a prototype with a mixture of inhouse manufactured parts and procured components. Finally, via experimental tests, the performance of the design and the control strategy are investigated. Certain drawbacks related to valve size and overall weight are observed in the prototype, which will be addressed in future studies.

Highly electro-responsive ionic soft actuator based on graphene nanoplatelets-mediated functional carboxylated cellulose nanofibers

Electro-responsive ionic soft actuators have attracted increasing interest owing to the promising applications for soft robots, biomimetic robots, active medical devices, flexible electronics, and wearable devices. However, existing ionic actuators still need a technology breakthrough for larger bending strain, faster response, and excellent actuation durability. Herein, we report a novel highly electro-responsive ionic actuator based on functional carboxylated cellulose nanofibers (CCNF) by doping with ionic liquid (IL) and graphene nanoplatelets (GN). The proposed CCNF-IL-GN actuator demonstrated a large tip displacement of 15.71 mm (peak-to-peak) at 2.0 V with 0.1 Hz, faster rise time (2.9s), broad frequency bandwidth (0.1–3.0 Hz), markedly reduced phase delay, and long actuation durability (98.6% retention for 3 h) without actuation response distortion, all of which were due to the fast-easy ion migration and massive charge transport ability of the designed ionically crosslinked electrolyte membrane, resulting from the strong ionic interactions and crosslinking of CCNF nanofibers with IL and GN. Furthermore, we investigated the actuator's bionic applications such as the bionic flower, bionic finger, and bionic window. These results elucidate the great potential of the designed CCNF-IL-GN actuators for bionic robots, soft robots, wearable electronics, and biomedical active devices.

Leveraging Bioinspired Structural Constraints for Tunable and Programmable Snapping Dynamics in High‐Speed Soft Actuators

AbstractCreating high‐speed soft actuators will have broad engineering and technological applications. Snapping provides a power‐amplified mechanism to achieve rapid movements in soft actuators that typically show slow movements. However, precise control of snapping dynamics (e.g., speed and direction of launching or jumping) remains a daunting challenge. Here, a bioinspired design principle is presented that harnesses a reconfigurable constraint structure integrated into a photoactive liquid crystal elastomer actuator to enable tunable and programmable control over its snapping dynamics. By reconfiguring constrained fin‐array‐shaped structure, the snapping dynamics of the structured actuator, such as launching or jumping angle and height, motion speed, and release force can be on‐demand tuned, thus enabling controllable catapult motion and programmable jumping. Moreover, the structured actuators exhibit a unique combination of ultrafast moving speed (up to 2.5 m s−1 in launching and 0.22 m s−1 in jumping), powerful ejection (long ejection distance of ≈20 cm, 35 mg ball), and high jumping height (≈8 cm, 40 times body lengths), which few other soft actuators can achieve. This study provides a new universal design paradigm for realizing controllable rapid movements and high‐power motions in soft matter, which are useful for building high‐performance soft robotics and actuation devices.

Dielectric elastomer actuators as artificial muscles for wearable robots

Current powered prosthetic and orthotic devices are mostly based on rigid actuators, which exhibit some intrinsic limitations, such as the reduced number of degrees of freedom, high weight, and limited flexibility. As progress is made in the soft robotics field, artificial muscles arise as potential candidates to replace current rigid actuator technologies. Dielectric elastomer actuators (DEAs) are a very promising class of soft actuator and are attracting attention due to their high energy density, fast response, and high actuation strains, similar or even superior to natural muscles. Such remarkable properties can lead the DEAs to be the next generation of actuators for wearable robots, and overcome the limitations imposed by the rigid actuators currently used. This paper reviews the state of art of the applications of DEAs to prostheses, orthoses, and rehabilitation devices. We analyzed the main configurations that are suitable as artificial muscles for the above-mentioned applications and presented the basic model of a dielectric elastomer transducer. When compared to the properties of natural skeletal muscle, some of these configurations stand out. However, there are still some drawbacks that prevent the large-scale application of DEAs, for instance the high operating voltages, durability issues, and nonlinearities that make them difficult to control. We investigated recent advances in materials, control strategies and fabrication methods that tackle these drawbacks, and they indicate that dielectric elastomers are great candidates to be the next generation of actuators for bionic devices.

Recent Advances in Piezoelectric Materials for Electromechanical Transducer Applications

Ferroelectricity has made a huge impact on science and technology since Joseph Valasek (then a Ph.D. student at the University of Minnesota) discovered it in 1920, a little longer than 100 years ago. Whereas Dr. Valasek’s original research was motivated by the need to develop seismic sensors, at present ferroelectric materials have been extensively studied for applications in high-energy capacitors, energy harvesting systems, night vision sensors, and electrocaloric solid cooling, and, of particular significance, the ferroelectrics are the material-of-choice for numerous electromechanical devices, including underwater acoustic transducers, medical diagnostic and therapeutic transducers, piezoelectric actuators, and ultrasonic motors, to name a few. The progress over the past 100 years has been enormous and it is ongoing: for example, the piezoelectric coefficient d of ferroelectrics has increased from a few pico-Coulomb per Newton to several thousand pico-Coulomb per Newton, which benefits all piezoelectric sensing and actuation devices.

Analysis of the elasto-magnetic wave propagation in a smart magnetostrictive actuator using a mesh-free method

This work aims to propose an implicit algorithm for solving the magnetoelastic wave propagation in a magnetostrictive actuator. This algorithm is built by combining meshless methods with the Newmark implicit time scheme. The mathematical formulation of vibrations of the actuator is performed by modeling the experimental actuator device by a monodimensional magnetostrictive cylindrical rod attached to an elastic spring, subjected to an axial magnetic field. The formulation of the problem is carried out using the rod model. The study is carried out taking into account mechanical and magnetic effects described by a linear model of strain-stress magnetoelastic relations, whose coefficients depend on the square of the magnetic field, elastic, magnetostrictive, and magnetoelastic characteristics of the elastomagnetic material of which the rod is made. The dynamic equation which describes the magnetoelastic wave propagation in the actuator is obtained by applying the Lagrangian formalism based on the least action principle. The wave propagation is governed by a spatio-temporal partial differential equation whose coefficients are a function of on elastic, magnetostrictive, and magnetic characteristics and implicitly depends on time. The resolution of the dynamic equation is made by adopting two numerical approaches developed by combining the mesh-free collocation methods, the Moving Least Squares (MLS), and the Radial Point Interpolation Method (RPIM) with the Newmark implicit scheme temporal integration. By performing the spatial discretization of the displacement, we obtain a system of linear second-order ordinary differential equations (ODEs), then transform it into a system of first-order ordinary differential equations after integrating Newmark’s implicit time scheme. A comparison of results computed by the proposed numerical approaches RPIM and MLS with experimental data available in the literature is presented. The stability and the solutions qualities of two meshless methods, RPIM and MLS, are also studied. The influence of magnetical and mechanical parameters as well as the coupling coefficients on the performance of the magnetostrictive actuator is also made.

A low-cost multilayer piezoelectric actuator for ultrasonic motor stator driving fabricated by a low-temperature co-fired ceramic process

Multilayer piezoelectric ceramics have wide application prospects in the fields of precision driving and intelligent sensing owing to their low driving voltages and large strains. However, high sintering temperatures and expensive noble metal electrodes limit their application as multilayer piezoelectric ceramic actuators (MLAs) in conventional devices. In this study, a modified piezoelectric ceramic powder and Ag inner electrode were used to prepare a low-cost MLA with a low sintering temperature of 900 °C. The MLA showed superior piezoelectric properties with d33 = 3015 pC/N and a large electric-field-induced strain of 0.13% at 22.2 kV/cm. Moreover, the stator of the ultrasonic motor composed of this MLA produced the ideal vibration mode, and the maximum rotation speed of the ultrasonic motor was 192 r/min under a 50 g load, which verifies the applicability of this component in practical minimised devices. These results demonstrate a strategy for fabricating low-cost and high-precision micro-actuators for precision driving.

Closed EWOD-based low-cost portable thermal detection system for point-of-care applications

Electrowetting-on-Dielectric (EWOD) is a powerful technology for biological and chemical diagnostics. It offers advantages of low sample volume, high sensitivity, high throughput and the possibility of automation. Of special interest is a miniaturization of a thermal detection system by utilizing the EWOD technique since it can minimize effort while reducing cost and the system size. The present study describes the development of a closed EWOD device for droplet actuation that is integrated with thermal cycling and optical diagnostics. Important steps, including sample and reagent transportation, merging and mixing, and color detection, are performed on the integrated platform. The thermal module uses heating as well as Peltier elements and K-type thermocouples with a PID controller to perform precise thermal cycling needed in clinical and medical diagnostics. Experimentally recorded temperature distribution that is realized in the closed EWOD configuration is numerically validated using the COMSOL simulator. The efficacy of the integrated system is experimentally demonstrated by performing Fehling’s test for glucose detection in a glycerin solution. Furthermore, the device is used to demonstrate the transportation of a liquid drop of blood mimicking liquid at a relatively high temperature of 90 °C. The system thus developed is reliable, providing real-time proof-of-concept and the feasibility of building a low-cost point-of-care EWOD device. • A portable closed EWOD based medical diagnostic system with thermal cycling is demonstrated. • Thermal management using heating and cooling element is integrated with the closed EWOD device. • Temperature distribution within the device is measured experimentally and validated against simulation. • Droplet motion is successfully realized over the temperature range studied, providing real-time proof-of-concept. • The system developed is tested by performing Fehling’s test for glucose detection.

Polymer-bonded magnets produced by laser powder bed fusion: Influence of powder morphology, filler fraction and energy input on the magnetic and mechanical properties

Bonded permanent magnets are key components in many energy conversion, sensor and actuator devices. These applications require high magnetic performance and freedom of shape. With additive manufacturing processes, for example laser powder bed fusion (LPBF), it is possible to produce bonded magnets with customized stray field distribution. Up to now, most studies use spherical powders as magnetic fillers due to their good flowability. Here, the behavior of large SmFeN platelets with a high aspect ratio as filler material and its influence on the arrangement and the resulting magnetic properties are examined in comparison to a spherical magnetic filler. The 3D distribution and orientation of the magnetic filler was studied by computed tomography and digital image analysis. The platelet-shaped particles align themselves perpendicular to the buildup direction during the process, which offers a new and cost-effective way of producing composites by LPBF with anisotropic structural and functional properties. The influence of LPBF parameters on the properties of the composites is investigated. Highest filling fractions are required for high magnetic remanence, however the powder itself limits this maximum due to particle shape and required minimal polymer fraction to form mechanically stable magnets. The coercivity decreases for higher filling fractions, which is attributed to increased rotation of insufficiently embedded magnetic particles in the matrix. It is discussed how filler morphology influences the observed change in coercivity since the rotation of spherical particles in comparison to platelet-shaped particles requires less energy. Our work shows the challenges and opportunities of large platelet shaped fillers used in LPBF for the production of anisotropic functional and structural composites.

Detecting Attacks and Locating Malicious Devices Using Unmanned Air Vehicles and Machine Learning

Internet access in both private and public environments allows users to broadly access their data what makes possible the deployment of new services based on Internet of Things. This fact created Smart Environments (SEs) that are composed of a huge amount of heterogeneous devices, for example, personal devices (smartphones, notebooks, tablets, etc) and IoT devices (sensors, actuators, and others). However, these environments can facilitate the action of malicious agents interested in promoting Distributed Denial of Service (DDoS) attacks to the network, and, when they are public places, it is challenging to locate these attackers. In this way, it is necessary to deploy solutions that can detect DDoS in SEs and to determine the physical location of the attacker, which is essential to prevent future attacks. Within this context, this article presents an Intelligent System for detection of DDoS and physical location of devices in SEs, applying Machine Learning (ML) and trilateration techniques. The experiments performed, using real network traffic and simulation, suggest that the proposed system is capable of detecting attacks and finding malicious devices.

Introducing concepts of passivity‐based control in anti‐windup algorithms

AbstractThis work presents a reference conditioning anti‐windup scheme based on passivity control theory. The main closed‐loop is controlled by a proportional–integral–derivative (PID) control, and the injection and damping assignment technique ensures that PID variables are compatible with the process input. In the proposed algorithm, a fictitious actuator, modeled as a first‐order filter, is incorporated to estimate the rate of change and the output of the actuator device. Amplitude and rate constraints are weight by coefficients that shape the energy function of the anti‐windup scheme. Finally, to show how the algorithm can cope with the windup problem, simulation results are presented. Even when shown the results on a linear PID, the proposal can extend to any linear or nonlinear control in the main control loop.

High-frequency magnetic energy loss based on J-A model for gallium iron alloy rod under variable stress conditions

Magnetostrictive rods have stress-sensitive properties. They are the core component of high-frequency high-power magnetostrictive sensor and actuator devices. In practical high frequency applications, a certain compressive stress needs to be applied to improve the magnetostrictive coefficient of the material. However, unsuitable operating conditions can lead to increased magnetic energy losses and deterioration of device performance. Therefore, the loss modelling as well as other physical behaviour of the material need to be investigated before designing magnetostrictive devices. This paper builds a test platform for high frequency magnetic properties of magnetostrictive materials. The high frequency magnetic properties of rod gallium iron alloy were measured and analyzed under different exciting conditions (different compressive stress σ, magnetic field frequency f, and magnetic field strength H). Then, based on the experimental data and the classical static J-A model, a high-frequency dynamic model for rod gallium iron alloy taking into account compressive stress was developed. The novelty of the model is that the variation pattern of the J-A model parameters with frequency and compressive stress is obtained by importing the experimental data into a parameter identification program written based on a hybrid particle swarm algorithm. The trend is fitted as a polynomial function of frequency and compressive stress to account for its effect on the magnetic properties of the material. The model can effectively predict the change of high frequency magnetic loss of materials under variable compressive stress conditions. Comparing the calculated values of magnetic energy loss with the measured ones show that the maximum error is 4.37% and the average error is 2.57%, which verifies the accuracy and feasibility of the model.

Using Deep Learning to Predict Minimum Foot–Ground Clearance Event from Toe-Off Kinematics

Efficient, adaptive, locomotor function is critically important for maintaining our health and independence, but falls-related injuries when walking are a significant risk factor, particularly for more vulnerable populations such as older people and post-stroke individuals. Tripping is the leading cause of falls, and the swing-phase event Minimum Foot Clearance (MFC) is recognised as the key biomechanical determinant of tripping probability. MFC is defined as the minimum swing foot clearance, which is seen approximately mid-swing, and it is routinely measured in gait biomechanics laboratories using precise, high-speed, camera-based 3D motion capture systems. For practical intervention strategies designed to predict, and possibly assist, swing foot trajectory to prevent tripping, identification of the MFC event is essential; however, no technique is currently available to determine MFC timing in real-life settings outside the laboratory. One strategy has been to use wearable sensors, such as Inertial Measurement Units (IMUs), but these data are limited to primarily providing only tri-axial linear acceleration and angular velocity. The aim of this study was to develop Machine Learning (ML) algorithms to predict MFC timing based on the preceding toe-off gait event. The ML algorithms were trained using 13 young adults’ foot trajectory data recorded from an Optotrak 3D motion capture system. A Deep Learning configuration was developed based on a Recurrent Neural Network with a Long Short-Term Memory (LSTM) architecture and Huber loss-functions to minimise MFC-timing prediction error. We succeeded in predicting MFC timing from toe-off characteristics with a mean absolute error of 0.07 s. Although further algorithm training using population-specific inputs are needed. The ML algorithms designed here can be used for real-time actuation of wearable active devices to increase foot clearance at critical MFC and reduce devastating tripping falls. Further developments in ML-guided actuation for active exoskeletons could prove highly effective in developing technologies to reduce tripping-related falls across a range of gait impaired populations.