Artificial Muscle Actuator Research Articles

Uncertain Quasi-static and Nonlinear Dynamic Analysis of Viscoelastic Dielectric Elastomer with Interval Parameters

Dielectric elastomers as a soft active material have been widely used in the field of artificial muscle actuator, acoustic actuator, loudspeaker, active control of vibration, soft robots and membrane resonators. Compared with traditional materials, there are many unknown uncertainties in the properties of the DE actuators. In this work, a viscoelastic dynamic model of dielectric elastomer is proposed with considering the uncertainties in material parameters, external mechanical load and voltage. By introducing the interval perturbation method and first-order Taylor series expansion method, the creep analysis, relaxation analysis and dynamic analysis of the dielectric elastomer with interval uncertain parameters are implemented. The effectivity of the proposed interval method is verified by the Monte Carlo simulation. This uncertain prediction method could be used in the design of active control systems with dielectric elastomers as actuators or sensors in the future.

Detailed Dynamic Model of Antagonistic PAM System and Its Experimental Validation: Sensorless Angle and Torque Control With UKF

This article proposes a detailed nonlinear mathematical model of an antagonistic pneumatic artificial muscle (PAM) actuator system for estimating the joint angle and torque using an unscented Kalman filter (UKF). The proposed model is described in a hybrid state-space representation. It includes the contraction force of the PAM, joint dynamics, fluid dynamics of compressed air, mass flows of a valve, and friction models. A part of the friction models is modified to obtain a novel form of the Coulomb friction depending on the inner pressure of the PAM. For model validation, offline and online UKF estimations and sensorless tracking control of the joint angle and torque are conducted to evaluate the estimation accuracy and tracking control performance. The estimation error is less than 7.91 %, and the steady-state tracking control performance is more than 94.75 %. These results confirm that the proposed model is detailed and could be used as the state estimator of an antagonistic PAM system.

Instability regions of pneumatic artificial muscle actuator subject to direct and parametric excitations

Instability regions of pneumatic artificial muscle actuator subject to direct and parametric excitations

Heterogeneous Thermochromic Hydrogel Film Based on Photonic Nanochains.

The rapid and robust response to external stimulus with a large volume deformation is of huge importance for the practical application of thermo-responsive photonic crystal film (TRPCF) in actuators, colorimetric sensors, and other color-related fields. Generally, decreasing the size of thermo-responsive photonic crystals and introducing micropores are considered to be two effective approaches to improve their responsiveness. However, they usually result in a poor mechanical property, which leads to optical instability. To solve these problems, a heterogeneous thermo-responsive photonic crystal film was developed here by integrating a thermosensitive hydrogel matrix poly(N-isopropylacrylamide-co-N-methylolacrylamide) (P(NIPAM-co-NHMA)) with high-modulus, but non-thermosensitive poly(acrylic acid -co-2-hydroxyethyl methacrylate (P(AA-co-HEMA)) hydrogel-based photonic nanochains (PNCs). The as-obtained TRPCF based on PNCs (TRPCF-PNC) well combined the rapid response and improved the mechanical property. Typically, it can complete a response within 12 s from 26 to 44 °C, which was accompanied by a larger deformation of the matrix than that of the PNCs. The unique rapid thermochromic mechanism of the TRPCF-PNC is revealed here. Furthermore, it exhibits a high tensible property along the PNC-orientation direction and excellent optical stability. The response time of the TRPCF-PNC can conveniently modulate by changing the cross-linking degree of the PNCs or the content of the thermosensitive component in the matrix. The heterogeneous TRPCF-PNC is believed to have potential applications in artificial muscle and quick-response actuation devices.

Pace Running of a Quadruped Robot Driven by Pneumatic Muscle Actuators: An Experimental Study

Our goal is to design a neuromorphic locomotion controller for a prospective bioinspired quadruped robot driven by artificial muscle actuators. In this paper, we focus on achieving a running gait called a pace, in which the ipsilateral pairs of legs move in phase, while the two pairs together move out of phase, by a quadruped robot with realistic legs driven by pneumatic muscle actuators. The robot is controlled by weakly coupled two-level central pattern generators to generate a pace gait with leg loading feedback. Each leg is moved through four sequential phases like an animal, i.e., touch-down, stance, lift-off, and swing phases. We find that leg loading feedback to the central pattern generator can contribute to stabilizing pace running with an appropriate cycle autonomously determined by synchronizing each leg’s oscillation with the roll body oscillation without a human specifying the cycle. The experimental results conclude that our proposed neuromorphic controller is beneficial for achieving pace running by a muscle-driven quadruped robot.

Cyber-secure pneumatic actuator system equipped with encrypted controller and attack detectors

A cyber-secure and flexible actuator is essential for cyber-physical-human systems. The use of wireless communication in such systems improves their usability but adds cybersecurity risks. This study proposes a cyber-secure flexible antagonistic pneumatic artificial muscle (PAM) actuator system. The proposed PAM actuator system has an encrypted proportional-integral controller and a real-time detector for cyberattacks. The controller is concealed in the encrypted control fashion using a homomorphic encryption scheme with security parameter 64 bit, and the control signal is computed over a cipher space. The detector has a threshold to detect significant changes in control inputs caused by cyberattacks such as signal injection and parameter falsification. The experimental results demonstrate that the proposed PAM actuator system achieves the desired control performance and improves the reliability of control operations under cyberattacks. The main contribution of this study is the first implementation of an encrypted controller for a pneumatic actuator to develop a secure PAM actuator with real-time detection of cyberattacks. The results of this study contribute to the future development of safe remote systems that interact with humans in the medical and industrial fields.

Sensorless angle and stiffness control of antagonistic PAM actuator using reference set

This paper proposes a simultaneous control method for the angle and stiffness of the joint in an antagonistic pneumatic artificial muscle (PAM) actuator system using only pressure measurements in the absence of an external force, and clarifies the allowable references for the PAM actuator system. To achieve a sensorless control, the proposed method estimates the joint angle and contraction forces using an unscented Kalman filter that employs a detailed model of the actuator system. Unlike the previous control methods, the proposed method does not require any encoder and force sensor to achieve angle and stiffness control of the PAM actuator system. Experimental validations using three control scenarios confirm that the proposed method can control the joint angle and stiffness simultaneously and independently. Moreover, it is shown that a reference admissible set can be used as an indicator to establish the reference values by demonstrating that the reference set covers the experimentally obtained trajectories of the angle and stiffness.

Hybrid Model Predictive Control of Floating Offshore Wind Turbines With Artificial Muscle Actuated Mooring Lines

Abstract Floating offshore wind turbines (FOWTs) are subject to undesirable platform motion and a significant increases in fatigue loads compared to their onshore counterparts. We have recently proposed using the fishing line artificial muscle (FLAM) actuators to realize active mooring line force control (AMLFC) for platform stabilization and thus load reduction, which features a compact design and no need for turbine redesign. However, as for the thermally activated FLAM actuators, a major control challenge lies in the asymmetric dynamics for the heating and the cooling half cycle of operation. In this paper, for a tension-leg platform (TLP) based FOWT with FLAM actuator based AMLFC, a hybrid dynamic model is obtained with platform pitch and roll degrees-of-freedom included. Then a hybrid model predictive control (HMPC) strategy is proposed for platform motion stabilization, with preview information on incoming wind and wave. A move blocking scheme is used to achieve reasonable computational efficiency. Fatigue, aerodynamics, structures, and turbulence (FAST) based simulation study is performed using the National Renewable Energy Laboratory (NREL) 5 MW wind turbine model. Under different combinations of wind speed, wave height and wind directions, simulation results show that the proposed control strategy can significantly reduce the platform roll and tower-base side-to-side bending moment, with a mild level of actuator power consumption.

Discrete-Time Sliding Mode Control based on Exponential Reaching Law of a Pneumatic Artificial Muscle Actuator

In this paper, a discrete-time sliding mode control (DSMC) approach based on exponential reaching law (ERL) is developed for a pneumatic artificial muscle (PAM) system to achieve high tracking performance and chattering alleviation. The proposed controller is designed based on an exponential term that dynamically adapts to the variation of the switching function, thus guarantees finite steps convergence and chattering phenomenon reduction simultaneously. Moreover, the effectiveness of the designed controller and its stability on a dual actuator PAM-driven system is demonstrated under various conditions. In addition, a leg-gait pattern is set as trajectory tracking for further validation. Finally, experiment results show that the proposed approach is effective and promising for rehabilitation applications.

Numerical Investigation on Vibration Performance of Flexible Plates Actuated by Pneumatic Artificial Muscle

This paper theoretically introduced the feasibility of changing the vibration characteristics of flexible plates by using bio-inspired, extremely light, and powerful Pneumatic Artificial Muscle (PAM) actuators. Many structural plates or shells are typically flexible and show high vibration sensitivity. For this reason, this paper provides a way to achieve active vibration control for suppressing the oscillations of these structures to meet strict stability, safety, and comfort requirements. The dynamic behaviors of the designed plates are modeled by using the finite element (FE) method. As is known, the output force vs. contraction curve of PAM is nonlinear generally. In this present finite element model, the maximum forces provided by PAM in different air pressure are adopted as controlling forces for applying for the plate. The non-linearity between the output force and displacement of PAM is avoided in this study. The dynamic behaviors of plates with several independent groups of controlling forces are observed and studied. The results show that the natural frequencies of the plate can be varying and the max amplitude decreases significantly if the controlling forces are applied. The present work also demonstrates the potential of the PAM actuators as valid means for damping out the vibration of flexible systems.

Initial-Rectification Barrier Iterative Learning Control for Pneumatic Artificial Muscle Systems With Nonzero Initial Errors and Iteration-Varying Reference Trajectories

Pneumatic artificial muscle actuators possess great potential in compliant rehabilitation devices since they are flexible and lightweight. The inherent high nonlinearities, uncertainties, hysteresis and time-varying characteristics in pneumatic artificial muscle systems brings much challenge for accurate system modeling and controller design. The angle tracking problem based on iterative learning control technology is considered in this work. This research proposes a new initial-rectification adaptive iterative learning control scheme for a pneumatic artificial muscle-actuated device with nonzero initial errors and iteration-varying reference trajectories. A barrier Lyapunov function is used to deal with the constraint requirement. A new initial rectification construction method is given to solve the nonzero initial error problem. Nonparametric uncertainties in the system are approximated by using a neural network, whose optimal weight is estimated by using difference learning method. As the iteration number increases, the system states of angle and angular velocity can accurately track the reference trajectories over the whole interval, respectively. In the end, the simulation results show excellent trajectory tracking performance of the iterative learning controller even if the reference trajectories are non-repetitive over the iteration domain.

Switching Control of Artificial Muscle Actuator with a Fluidic Switching Valve using Coanda Effect

Switching Control of Artificial Muscle Actuator with a Fluidic Switching Valve using Coanda Effect

Self-Induced Vibration Mechanism with Artificial Muscle Actuator Driven by Pressure

Self-Induced Vibration Mechanism with Artificial Muscle Actuator Driven by Pressure

Ethanol Phase Change Actuator Based on Thermally Conductive Material for Fast Cycle Actuation.

Artificial muscle actuator has been devoted to replicate the function of biological muscles, playing an important part of an emerging field at inter-section of bionic, mechanical, and material disciplines. Most of these artificial muscles possess their own unique functionality and irreplaceability, but also have some disadvantages and shortcomings. Among those, phase change type artificial muscles gain particular attentions, owing to the merits of easy processing, convenient controlling, non-toxic and fast-response. Herein, we prepared a silicon/ethanol/(graphene oxide/gold nanoparticles) composite elastic actuator for soft actuation. The functional properties are discussed in terms of microstructure, mechanical properties, thermal imaging and mechanical actuation characteristics, respectively. The added graphene oxide and Au nanoparticles can effectively accelerate the heating rate of material and improve its mechanical properties, thus increasing the vaporization rate of ethanol, which helps to accelerate the deformation rate and enhance the actuation capability. As part of the study, we also tested the performance of composite elastomers containing different concentrations of graphene oxide to identify GO-15 (15 mg of graphene oxide per 7.2 mL of material) flexible actuators as the best composition with a driving force up to 1.68 N.

Biomimetic cell-actuated artificial muscle with nanofibrous bundles

Biohybrid artificial muscle produced by integrating living muscle cells and their scaffolds with free movement in vivo is promising for advanced biomedical applications, including cell-based microrobotic systems and therapeutic drug delivery systems. Herein, we provide a biohybrid artificial muscle constructed by integrating living muscle cells and their scaffolds, inspired by bundled myofilaments in skeletal muscle. First, a bundled biohybrid artificial muscle was fabricated by the integration of skeletal muscle cells and hydrophilic polyurethane (HPU)/carbon nanotube (CNT) nanofibers into a fiber shape similar to that of natural skeletal muscle. The HPU/CNT nanofibers provided a stretchable basic backbone of the 3-dimensional fiber structure, which is similar to actin-myosin scaffolds. The incorporated skeletal muscle fibers contribute to the actuation of biohybrid artificial muscle. In fact, electrical field stimulation reversibly leads to the contraction of biohybrid artificial muscle. Therefore, the current development of cell-actuated artificial muscle provides great potential for energy delivery systems as actuators for implantable medibot movement and drug delivery systems. Moreover, the innervation of the biohybrid artificial muscle with motor neurons is of great interest for human-machine interfaces.

Numerical and Experimental Study of a Flexible Trailing Edge Driving by Pneumatic Muscle Actuators

A static aeroelastic analysis of the flexible trailing edge is conducted to calculate the deformed shape, aerodynamic coefficients and corresponding driving pressure. A physical flexible trailing edge model is manufactured using a honeycomb structure, which is measured based on binocular vision. The quadratic response surface method is adopted to establish the pneumatic artificial muscle actuator model. The wire-pulley transmission model is built to identify the existence of equivalent forces and produce the equivalent forces as the substitute of actuation force. A finite element model of the flexible trailing edge is established, which is validated by the test data. A nonlinear relationship is found between the driving pressure and deflection angle. The pressure needed to bear the structural stiffness is found to be much larger than that of the aerodynamic load. With the increase in pressure, the magnitude of the lift coefficient increases less. However, the magnitude of the drag coefficient increases more with the increase in pressure under 0.2 MPa. When the driving pressure exceeds 0.2 MPa, the relationship between them is nearly linear.

Shape- and Color-Switchable Polyurethane Thermochromic Actuators Based on Metal-Containing Ionic Liquids.

Many creatures have excellent control over their form, color, and morphology, allowing them to respond to the interaction of environmental stimuli better. Here, the bioinspired synergistic shape-color-switchable actuators based on thermally induced shape-memory triethanolamine cross-linked polyurethane (TEAPU) and thermochromic ionic liquids (ILs) were prepared. The thermochromic ILs with various metalized anions, including bis(1-butyl-3-methylimidazolium) tetrachloro nickelate ([Bmim]2[NiCl4]) and bis(1-butyl-3-methylimidazolium) tetrachloride cobalt ([Bmim]2[CoCl4]), are investigated. The actuators exhibit thermochromic response, as evidenced by a shift in the color of the composites, which is due to the formation of the tetrahedral complex MCl42- (M = Ni and Co) after dehydration. The shape-color-switchable thermochromic actuators have strong molecular interaction between TEAPU and ILs and can mimic natural flowers and change the color and shape quickly in a narrow temperature range (30-70 °C). In addition, these thermochromic actuators can lift more than 50 times their weight and withstand strains of more than 1100%. The results represent the potential application in artificial muscle actuators and intelligent camouflages.

Modified Stiffness-Based Soft Optical Waveguide Integrated Pneumatic Artificial Muscle (PAM) Actuators for Contraction and Force Sensing

This article presents design, fabrication, characterization, and experimental verification of a new sensing method (soft optical sensing) for pneumatic artificial muscle (PAM) actuators. Soft optical waveguides are designed and fabricated using the proposed modified stiffness concept for soft sensors. The design of the sensor allows us to measure both contraction and force of a PAM actuator under loaded conditions. This proposed method makes it possible to have a highly sensitive actuator system with linear contraction sensing. The sensorized PAMs are supposed to work in high-pressure applications with the ability to be used repeatedly without significant degradation in signal quality. To characterize and validate the proposed method, two PAM actuators make use of two separately designed test systems to plot and model the characteristic curves. Finally, the validation for control is provided using measured sensor data as feedback to the controller.

Theoretical Control-Centric Modeling for Precision Model-Based Sliding Mode Control of a Hydraulic Artificial Muscle Actuator

Abstract Artificial muscles (AMs) traditionally rely on pneumatic sources of fluid power. The use of hydraulics can increase the power and force to weight and volume ratios of AM actuators. This paper develops a control-centric third-order single-input single-output (SISO) lumped-parameter dynamic model and sliding mode position controller based on Filippov's principle of equivalent dynamics for a braided hydraulic artificial muscle (HAM) actuator. The model predicts the nonlinear behavior of the HAM free contraction and captures the fluid and actuator nonlinear dynamic interactions in addition to the braid deformation. Model simulations are compared to experimental results for quasi-static pressurization, isometric pressurization, and open-loop square wave commands at 0.25, 0.5, and 1 Hz. Experiments of sine wave tracking at 0.25, 0.5, and 1 Hz and continuous square wave tracking at 0.067 Hz are conducted using a sliding mode controller (SMC) derived from the model. The SMC achieves a steady-state error of 6 μm at multiple setpoints within the actuator's 17 mm stroke. Compared to a proportional-integral-derivative (PID) controller, the SMC root-mean-square (RMS) error, mean error, and absolute maximum error are reduced on average by 53%, 61%, and 44%, respectively, demonstrating the benefit of model-based approaches for controlling HAMs.

Automated Routing of Muscle Fibers for Soft Robots

This article introduces a computational approach for routing thin artificial muscle actuators through hyperelastic soft robots, in order to achieve a desired deformation behavior. Provided with a robot design and a set of example deformations, we continuously co-optimize the routing of actuators, and their actuation, to approximate example deformations as closely as possible. We introduce a data-driven model for McKibben muscles, modeling their contraction behavior when embedded in a silicone elastomer matrix. To enable the automated routing, a differentiable hyperelastic material simulation is presented. Because standard finite elements are not differentiable at element boundaries, we implement a moving least squares formulation, making the deformation gradient twice differentiable. Our robots are fabricated in a two-step molding process, with the complex mold design steps automated. While most soft robotic designs utilize bending, we study the use of our technique in approximating twisting deformations on a bar example. To demonstrate the efficacy of our technique in soft robotic design, we show a continuum robot, a tentacle, and a four-legged walking robot.