Smart Material Actuators Research Articles

A constitutive artificial neural networks-based mechanical model of the pneumatic artificial muscles

Abstract Pneumatic artificial muscles (PAMs), recognized as typical smart material actuators, have perennially presented a formidable challenge in the realm of precise mechanical modeling due to the hyperelasticity and nonlinearity. In order to construct the mechanical model of the PAM, we propose a constitutive artificial neural network-based mechanical model. Utilizing the constitutive artificial neural network (CANN), we have constructed a strain energy function for PAMs that satisfies symmetry, objectivity, and polyconvexity. Furthermore, by employing the principle of virtual work and considering the hyper-elastic material, the geometric constraints, and the deformation of the internal air chamber, we have derived the mechanical model of PAMs. To verify the accuracy of the proposed model, the finite element simulation is used to demonstrate the modeling accuracy under different load conditions for PAMs with different geometries and constitutive model conditions. Finally, the accuracy and generalization of the proposed model is validated through experiments on a PAM experimental platform.

Solid-State Electromechanical Smart Material Actuators for Pumps—A Review

Solid-state electromechanical smart material actuators are versatile as they permit diverse shapes and designs and can exhibit different actuation modes. An important advantage of these actuators compared to conventional ones is that they can be easily miniaturized to a sub-millimeter scale. In recent years, there has been a great surge in novel liquid pumps operated by these smart material actuators. These devices create opportunities for applications in fields ranging from aerospace and robotics to the biomedical and drug delivery industries. Although these have mainly been prototypes, a few products have already entered the market. To assist in the further development of this research track, we provide a taxonomy of the electromechanical smart material actuators available, and subsequently focus on the ones that have been utilized for operating pumps. The latter includes unidirectional shape memory alloy-, piezoelectric ceramic-, ferroelectric polymer-, dielectric elastomer-, ionic polymer metal composite- and conducting polymer-based actuators. Their properties are reviewed in the context of engineering pumps and summarized in comprehensive tables. Given the diverse requirements of pumps, these varied smart materials and their actuators offer exciting possibilities for designing and constructing devices for a wide array of applications.

Screening significant properties of macro-fiber composite laminate substrate anisotropy with viscoelastic and thermal considerations at the quasi-static level

A macro-fiber composite (MFC) is a class of smart material actuator that employs piezoceramic fibers to extend or contract under an applied electric field. When embedded on a thin substrate, actuated MFCs induce surface pressure, resulting in out-of-plane motion. Design characteristics of the substrate, such as anisotropy, give rise to unique bend/twist behavior. Previous studies on MFC applications have focused on optimizing patch location in relation to the local design to achieve optimal bend/twist motion. However, the resolution to these approaches is restricted to the design space of the application, presenting an absence in piezoelectric laminate design intuition. This research aims to streamline the initial optimization process by analyzing the significant material properties associated with substrate design. To accomplish this, a viscoelastic piezoelectric plate theory model is developed to accurately capture the displacement behavior of the MFC laminate for any given substrate design. Experimental data is used to validate and refine the model, ensuring it closely represents real-world physics. A 2k fractional factorial design of experiments approach is used to identify significant substrate properties per MFC laminate configuration, assigning each material property a two-level coding system. Three configurations are observed, with each exhibiting distinct significant properties and effects compared to others. Furthermore, the study explores the impact of thermal factors on substrate behavior for these MFC laminates, highlighting how significant properties can be temperature dependent. The contributions to the kinematic response due to substrate property perturbation varies uniquely per material property and MFC laminate configuration. Statistical evidence supports the notion that the hysteretic behavior of a material is unaffected by thermal influences and is solely determined by the elastic constants of the substrate. The maximum remanent hysteretic response is shown to be proportional to the maximum actuation response at near room temperature.

Robust output regulation of a class of smart actuators described by a minimum phase LPV dynamics

This paper presents a new control strategy for a class of minimum phase linear parameter-varying (LPV) systems representative of smart material actuators. In position control applications of such devices, one is typically interested in achieving output regulation with an arbitrary exponential decay rate. In principle, this problem can be tackled by assigning an exponential decay rate to the full system state, by means of well-established linear matrix inequalities (LMI) methods. For the class of systems under investigation, however, this approach leads to excessively large controller gains in case the desired decay rate is faster than the open-loop zero dynamics. In addition, the existence of unmeasurable state variables related to the material microstructure makes it not possible to directly implement full state feedback laws which are commonly adopted in LPV theory. To overcome these issues, a new design strategy is proposed. The key idea relies on arbitrarily shaping the output exponential decay rate without requiring fast convergence of the full state vector. This goal is achieved by means of a partial state feedback control law which solely depends on the measurable system states. A LMI algorithm is also developed to systematically address the design of the partial state feedback controller. The method is validated by means of simulations on generic examples, as well as via experiments on a mechatronic positioning system based on a dielectric elastomer membrane. In case the desired output convergence speed is faster than the open-loop zero dynamics, it is shown that the new approach leads to better transient behaviors and significantly smaller controller gains than standard LPV design techniques.

Perceptual Soft End-Effectors for Future Unmanned Agriculture.

As consumers demand ever-higher quality standards for agricultural products, the inspection of such goods has become an integral component of the agricultural production process. Unfortunately, traditional testing methods necessitate the deployment of numerous bulky machines and cannot accurately determine the quality of produce prior to harvest. In recent years, with the advancement of soft robot technology, stretchable electronic technology, and material science, integrating flexible plant wearable sensors on soft end-effectors has been considered an attractive solution to these problems. This paper critically reviews soft end-effectors, selecting the appropriate drive mode according to the challenges and application scenarios in agriculture: electrically driven, fluid power, and smart material actuators. In addition, a presentation of various sensors installed on soft end-effectors specifically designed for agricultural applications is provided. These sensors include strain, temperature, humidity, and chemical sensors. Lastly, an in-depth analysis is conducted on the significance of implementing soft end-effectors in agriculture as well as the potential opportunities and challenges that will arise in the future.

Adaptive Pseudoinverse Control for Constrained Hysteretic Nonlinear Systems and its Application on Dielectric Elastomer Actuator

Flexible smart material actuators, such as dielectric elastomer actuators (DEA) and ionic polymer metal composites, have shown greatly potential applications in the field of soft biomimetic robots and rehabilitation robots due to their human-like muscle softness, large stretch, and high energy density characteristics. In this article, a fuzzy logic system (FLS) and barrier Lyapunov function (BLF) based adaptive pseudoinverse control scheme is proposed for a class of state-constrained hysteretic nonlinear systems, where all the states are always strictly limited in each constrained set. The main features of this article are: 1) the hysteresis nonlinearity in the actuators is considered and mitigated by the proposed pseudoinverse control algorithms, which implies that the direct hysteresis inverse model is not required, instead a searching mechanism of the actual control signal from the temporary control signal; 2) the all-state-constrained control problem of the Preisach hysteresis model is overcome when the control signal is coupled in the double integral functions with the aid of an FLS, BLFs, and the proposed hysteresis pseudoinverse algorithms; and 3) the DEA-based motion control platform is constructed, and the experiments are conducted to validate the effectiveness of our proposed control scheme.

Research on the Vibration Reduction Mechanism of a New Tensioning Platform with an Embedded Superstructure

Aiming at the problem of precision driving and vibration suppression for sensitive payloads on-orbit, this paper proposes a new compliant platform based on an embedded superstructure and a smart material actuator. Firstly, the main structure of the platform is designed and optimized to achieve the expected indicators via the response surface method. Then, the vibration reduction mechanism of the platform with the embedded superstructure is studied by establishing an equivalent model. Following that, a four-phase superstructure is matched and designed with a compact space, and the results are verified by finite element modal analysis. Finally, both the tensioning performance and vibration reduction performance under fixed frequency harmonic disturbance are studied via transient dynamic simulation. Based on the obtained results, directions for future improvements are proposed. The relevant conclusions can provide a reference for function integration of precision tensioning and vibration suppression.

Modeling and Adaptive Output Feedback Control of Butterfly-Like Hysteretic Nonlinear Systems With Creep and Their Applications

This paper proposes a novel robust adaptive piecewise- indirect inverse output- feedback control scheme to mitigate butterfly-like hysteresis with creep in smart-material actuators. Piecewise-indirect inverse indicates that it is not a true hysteresis and creep inverse compensatorbut an on-line decoupling mechanism to accessing the approximately actual control signal from the designed hysteretic and creeping temporary control signal. In addition, a new butterfly-like relay operator is proposed for the first time, leading to the construction of a new model of butterfly-like hysteresis with creep. Finally, the experimental results on the dielectric elastomer actuator motion control platform illustrate the effectiveness of the proposed output-feedback control scheme.

Safety-Critical Control Systems [About this Issue

This issue of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Control Systems</i> includes one feature and one lecture note. In the feature, “Runtime Assurance for Safety-Critical Systems: An Introduction to Safety Filtering Approaches for Complex Control Systems” <xref ref-type="list-item" rid="list-itemA1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[A1]</xref> , authors Kerianne L. Hobbs, Mark L. Mote, Matthew C.L. Abate, Samuel D. Coogan, and Eric M. Feron provide an introductory tutorial of runtime assurance (RTA) concepts and their role in ensuring safety of complex control systems. Assuming an undergraduate-level understanding of control theory and state-space concepts, this article provides theory and examples for RTA architectures, four types of RTA approaches, and a number of systems engineering and practical considerations for employing RTA in safety-critical, cyberphysical systems. In the “Lecture Notes” column, “The Prandtl-Ishlinskii Hysteresis Model: Fundamentals of the Model and Its Inverse Compensator,” <xref ref-type="list-item" rid="list-itemA2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[A2]</xref> Mohammad Al Janaideh, Mohammad Al Saaideh, and Xiaobo Tan introduce the mathematical formulations of the Prandtl–Ishlinskii (PI) and Generalized PI (GPI) hysteresis models as well as their analytical inverses. These models can effectively characterize hysteresis nonlinearities in various systems, especially smart-material actuators, and their inverses can be used in feedforward compensation to mitigate the effect of hysteresis. Numerical examples of the PI and GPI models as well as their analytical inverses are also included in the article. The intended audience includes graduate students and researchers from academia and industry interested in hysteresis modeling and compensation.

Implementation of Smart Materials for Actuation of Traditional Valve Technology for Hybrid Energy Systems

The ever-changing nature of the power industry will require the implementation of hybrid energy systems. Integration of tightly coupled components in hybrids often involves the diversion of exhaust gas flow. An innovative smart material actuation technology is proposed to replace traditional electro-mechanical actuated valve mechanisms with lighter and less expensive actuators. A shape memory alloy (SMA) spring-actuated valve was designed for high-temperature service to demonstrate the promise of smart materials in control valve applications. With SMA springs only generating a maximum force of 3.2 N, an innovative valve design was necessary. To demonstrate the concept, a 3-inch Nominal Pipe Size valve was designed, and 3D printed using the stereolithography technique. Increasing the electrical current to actuate the SMA springs reduced actuation time. The maximum current of 10 A produced the lowest actuation time of 2.85 s, with an observed maximum stroke rate of more than 100 stroke completion %/s (considering actuation open/close as 100% stroke) at the midrange. The final assembly of the valve was estimated to provide a cost reduction of more than 30% and a weight reduction of more than 80% compared to the other available automatic valves in the present market.

Deep reinforcement learning achieves multifunctional morphing airfoil control

Smooth camber morphing aircraft offer increased control authority and improved aerodynamic efficiency. Smart material actuators have become a popular driving force for shape changes, capable of adhering to weight and size constraints and allowing for simplicity in mechanical design. As a step towards creating uncrewed aerial vehicles (UAVs) capable of autonomously responding to flow conditions, this work examines a multifunctional morphing airfoil’s ability to follow commands in various flows. We integrated an airfoil with a morphing trailing edge consisting of an antagonistic pair of macro fiber composites (MFCs), serving as both skin and actuator, and internal piezoelectric flex sensors to form a closed loop composite system. Closed loop feedback control is necessary to accurately follow deflection commands due to the hysteretic behavior of MFCs. Here we used a deep reinforcement learning algorithm, Proximal Policy Optimization, to control the morphing airfoil. Two neural controllers were trained in a simulation developed through time series modeling on long short-term memory recurrent neural networks. The learned controllers were then tested on the composite wing using two state inference methods in still air and in a wind tunnel at various flow speeds. We compared the performance of our neural controllers to one using traditional position-derivative feedback control methods. Our experimental results validate that the autonomous neural controllers were faster and more accurate than traditional methods. This research shows that deep learning methods can overcome common obstacles for achieving sufficient modeling and control when implementing smart composite actuators in an autonomous aerospace environment.

Development and Characteristic Investigation of a Multidimensional Discrete Magnetostrictive Actuator

Active combustion control (ACC) has been proved to be an effective method for the suppression of pressure oscillation in aero engine combustion chambers, which will seriously endanger flight safety of aircrafts. However, the actuators for ACC need to work with a bandwidth of 1000 Hz, a stroke up to submillimeter level and a high power density simultaneously. Existing electromagnetic actuators, or smart material actuators, are still unable to meet these requirements at the same time. To address this issue, in this article, a multidimensional discrete magnetostrictive actuator (MDMA) was developed by adopting the multidimensional discrete configuration. In order to obtain large output displacement while maintaining the characteristics of high bandwidth and high power density of magnetostrictive materials, tubular and cylindrical magnetostrictive rods are nested axially and radially through sleeves to form a discrete magnetostrictive stack; independent excitation coils and permanent magnet rings are integrated axially to form a discrete electromagnetic excitation system. Then, a magnetic equivalent circuit (MEC) model was developed to analyze the magnetic field distribution characteristic of MDMA components. Next, a multiphysics comprehensive dynamic model was established to describe the complex dynamic properties of multidimensional discrete structures. Subsequently, a prototype of the MDMA was fabricated, which is only 56 mm in diameter and only 71.5 mm high. Experimental results indicate that, the proposed MDMA reaches a stoke of 100 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> m, and the working bandwidth can exceed 1000 Hz. Furthermore, closed-loop control tests were conducted and the results showed that the MDMA can effectively track sinusoidal references of different amplitudes under low frequency with a feedback PID controller.

Hysteresis online identification approach for smart material actuators with different input signals and external disturbances

Hysteresis online identification approach for smart material actuators with different input signals and external disturbances

Development and Test of a Two-Dimensional Stacked Terfenol-D Actuator With High Bandwidth and Large Stroke

Smart material actuators (SMAs) can provide motion with high resolution and high bandwidth, but the output stroke is relatively small. Therefore, motion amplification mechanisms for SMAs have drawn considerable attentions in recent years. However, most of existing mechanisms realize the motion amplification at the expense of working bandwidth. To achieve large stroke and high bandwidth simultaneously, a novel two-dimensional stacked magnetostrictive actuator (TSMA) was developed and tested by adopting the magnetostrictive material, i.e., the Terfenol-D in this article. The U-shaped sleeves were employed to support the axial and radial two-dimensional stacking of three Terfenol-D rods. Then, an analytical model was established based on working principle of the TSMA, and a design of experiment analysis was carried out for the sensitivity study of the TSMA's key structural parameters. Next, the involved parameters of the established analytical model were obtained via system identification. Furthermore, several experimental tests of a fabricated prototype for the TSMA were carried out. The results show that the stroke of the proposed TSMA can reach 65 μ m. The displacement amplification ratio is achieved as 2.8 and the working bandwidth is kept as 500 Hz. This proves that the proposed structure can significantly increase the displacement with a little loss of bandwidth. Finally, a set of preliminary closed-loop tests using a traditional incremental proportion-integration-differentiation (PID) control were carried out to improve the motion precision. The closed-loop tracking results of 10-100 Hz sinusoid references show that the root-mean-square errors are less than 4$\%$ using a simple PID control alone.

Adaptive Parameter Estimation With Convergence Analysis for the Prandtl–Ishlinskii Hysteresis Operator

Abstract Hysteresis is a nonlinear characteristic ubiquitously exhibited by smart material sensors and actuators, such as piezoelectric actuators and shape memory alloys. The Prandtl–Ishlinskii (PI) operator is widely used to describe hysteresis of smart material systems due to its simple structure and the existence of analytical inverse. A PI operator consists of a weighted superposition of play (backlash) operators. While adaptive estimation of the weights for PI operators has been reported in the literature, rigorous analysis of parameter convergence is lacking. In this article, we establish persistent excitation and thus parameter convergence for adaptive weight estimation under a rather modest condition on the input to the PI operator. The analysis is further supported via simulation, where a recursive least square (RLS) method is adopted for parameter estimation.

Adaptive Estimation of Play Radii for a Prandtl–Ishlinskii Hysteresis Operator

The Prandtl–Ishlinskii (PI) operator is a mathematical model for hysteresis, and it is comprised of weighted superposition of multiple play (backlash) operators. The PI operator has been widely used in modeling and compensation of hysteresis in smart material actuators, robots, and mechanical systems. The behavior of a PI operator is determined by both the weights and the radii of individual play operators. However, existing modeling work has mostly been focused on the identification of the weight parameters by assuming the play radii to be known. While the latter approach is convenient due to the linear relationship between the operator output and the weight parameters, it often requires a large number of plays with preassigned radii in order to adequately capture the hysteresis in a given application. In this work, for the first time, we propose an adaptive estimation algorithm to identify the play radii of a PI operator, to enable accurate modeling of hysteresis with a small number of plays and, thus, reduce the complexity in control. The major challenge lies in the nonlinear, complex, time-varying relationship between the PI operator output and the play radii. The proposed algorithm utilizes available measurement and information, including the instantaneous slope of the hysteretic input–output graph, to derive a modified estimation error function that is proportional to the parameter error. With a mild condition on the input, we establish the persistent excitation of the resulting regressor vector and the parameter convergence under a gradient algorithm with parameter projection. Both simulation and experimental results are presented to illustrate the proposed approach. In particular, comparison results based on experimental data from a piezoelectric nanopositioner show that, with the proposed method, the resulting PI operator outperforms identified PI operators of larger numbers of plays with preassigned radius values.

Modelling and Closed–loop Control System for Magnetorheological Elastomer Linear Actuator

Controlling the actuator in micro to microscale positioning is the challenge in the development of smart material actuator. The design of the existing commercial piezoelectric actuator is limited due to the material properties itself such as brittle which require special packaging and protection in order to avoid creep occurred. Magnetorheological linear actuator representing a relative new class in actuator development. the flexibility in MRE material potentially overcome the limitation of the piezoelectric actuator. This paper presenting the development of closed loop control system including the dynamic model, plant model and PID controller for linear MRE actuator. The control system was successfully developed and the MRE linear actuator able to generate the displacement at certain steady state error.

Smart material actuators as a contributor for IoT-based smart applications and systems: Analyzing prototype and process measurement data of shape memory actuators for reliability and risk prognosis

Smart material actuators as a contributor for IoT-based smart applications and systems: Analyzing prototype and process measurement data of shape memory actuators for reliability and risk prognosis

Experimental investigation on a flapping beam with smart material actuation for underwater application

This paper presents an experimental investigation of flapping beam for thrust generation. The beam is studied in current of water and actuated by the “Macro-Fiber Composite (MFC)” based smart material to undergo flapping and undulatory motions, mimicking a fish. The results obtained are expected to be useful in designing process of robotic fish in different marine environment. Herein, the average power spent for actuation is measured and it is observed that the maximum efficiency obtained is 55% for the frequency of 2.0 Hz. The set of experiment of the undulatory smart beam conducted at different depths of submergence showed that an increase in depth of submergence lead to increase of the thrust. However, in the region between the free surface and bottom of the channel (i.e. mid-depth) the thrust is low. By analyzing the measured data, threshold value of “Elastio-Inertia” number for low input power and high efficiency is determined. The results obtained are expected to help in better understanding the swimming pattern, locomotion of fish and other sea creatures. Also, it contributes to the design and development of motor-less and gearless thrust generation mechanisms for the marine vehicles and robots.

Tailored Magnetic Springs for Shape-Memory Alloy Actuated Mechanisms in Miniature Robots

Animals can incorporate large numbers of actuators because of the characteristics of muscles; whereas, robots cannot, as typical motors tend to be large, heavy, and inefficient. However, shape-memory alloys (SMA), materials that contract during heating because of change in their crystal structure, provide another option. SMA, though, is unidirectional and therefore requires an additional force to reset (extend) the actuator, which is typically provided by springs or antagonistic actuation. These strategies, however, tend to limit the actuator's work output and functionality as their force–displacement relationships typically produce increasing resistive force with limited variability. In contrast, magnetic springs—composed of permanent magnets, where the interaction force between magnets mimics a spring force—have much more variable force–displacement relationships and scale well with SMA. However, as of yet, no method for designing magnetic springs for SMA-actuators has been demonstrated. Therefore, in this paper, we present a new methodology to tailor magnetic springs to the characteristics of these actuators, with experimental results both for the device and robot-integrated SMA-actuators. We found magnetic building blocks, based on sets of permanent magnets, which are well-suited to SMAs and have the potential to incorporate features such as holding force, state transitioning, friction minimization, auto-alignment, and self-mounting. We show magnetic springs that vary by more than 3 N in 750 $\mu$ m and two SMA-actuated devices that allow the MultiMo-Bat to reach heights of up to 4.5 m without, and 3.6 m with, integrated gliding airfoils. Our results demonstrate the potential of this methodology to add previously impossible functionality to smart material actuators. We anticipate this methodology will inspire broader consideration of the use of magnetic springs in miniature robots and further study of the potential of tailored magnetic springs throughout mechanical systems.