Pneumatic Muscle Research Articles

Artificial-Hand Technology—Current State of Knowledge in Designing and Forecasting Changes

The subject of human-hand versatility has been intensively investigated for many years. Emerging robotic constructions change continuously in order to mimic natural mechanisms as accurately as possible. Such an attitude is motivated by the demand for humanoid robots with sophisticated end effectors and highly biomimic prostheses. This paper provides wide analysis of more than 80 devices that have been created over the last 40 years. It compares both the mechanical structure and various actuators from conventional DC motors and servomechanisms, through pneumatic muscles, to soft actuators and artificial muscles. Described measured factors include angles, forces, torques, tensions, and tactiles. Furthermore, the appropriate statistics of kinematic configuration, as well as the type or number of drive units and sensory systems, show not only recent problems, but also trends that will be followed in the future.

Design of Hybrid Phase Sliding Mode Control Scheme for Lower Extremity Exoskeleton

Aiming at a pneumatic artificial muscle (PAM) lower extremity exoskeleton, a control mechanism based on hybrid phase sliding mode control (SMC) is proposed. First of all, the human gait cycle is mainly divided into the swing phase and stance phase, and the lower extremity exoskeleton phase models are established by the Euler–Lagrange method, respectively. Secondly, the lower limb exoskeleton is inevitably affected in the diverse working environment, and the exoskeleton model has nonlinear and strong coupling characteristics, which both increase the control difficulty. In this situations, a robust sliding mode control method is designed based on an Extended State Observer (ESO). Thirdly, the pneumatic muscle takes time to contract and relax, and then the joint input torque cannot jump when the gait phase changes, hence, the smoothing switching of the assistive control scheme is introduced to solve it. The smoothing switching time is detected by a phase detector, and the phase detector is designed by the plantar pressure information. Finally the comparative simulation shows that this control strategy has the advantages of fast time, high control precision and no jump during control torque switching. Pneumatic artificial muscle contraction rate curve shows that the pneumatic muscles’ motion range meets the control requirement of the exoskeleton.

Experimental Evaluation of A Cylinder Actuator Control using McKibben Muscle

There has been an increased interest in applying pneumatic muscle actuator (PMA) in robotic systems because of its low weight and high compliant characteristics. On the other hand, pneumatic muscle actuator (PMA) is gaining attention in robotic applications because of its low weight and high compliant characteristics. It is known that the McKibben muscle is different from the fluidic cylinder actuator in that the cylinder was unstable in its position and in its velocity in an open-loop system unlike the McKibben that is stable in its position. The modeling and control of McKibben muscle as the actuator for the cylinder are crucial because it is known to have non-linear response, hysteresis and small stroke. In this project, a single acting cylinder model which would have uncontrolled extension to push direction by compressed air, is actuated and controlled using a PMA. The system is designed with two 1.3mm-diameter McKibben muscles attached to the cylinder. Open loop control was used and the result shows that the PMA is able to control the cylinder with good performance.

Evaluation of MRI-compatible pneumatic muscle stepper motors

Abstract The automation of instruments and tools (e.g. bone drill) or robotic devices (e.g. needle positioning robot for prostate surgery) for use in interventional MRI (iMRI) is still challenging due to a lack of accurate, affordable and completely metal-free actuators and motors. Inspired by biological muscles, a bionic equivalent known as the fluid muscle actuator (which can be operated pneumatically or hydraulically) is well-known in the mechanical engineering industry. Fluid muscle actuators have multiple beneficial characteristics: they are simple, self-returning, low-friction and can produce relatively high actuation forces at low diameters and pressures. We present two novel designs for metal-free, pneumatic stepper motors for potential application in iMRI. Our stepper motors are powered by simple pneumatic muscles, which are assembled from low-cost off-the-shelf components. Besides, the components of the stepper motor demonstrators were 3Dprinted using a stereolithographic additive manufacturing process (SLA printing). We evaluate the effect of pneumatic muscle length on contractile force and length. Our results demonstrated the functional feasibility of the pneumatic muscle-powered and fully MRI-compatible stepper motor designs. In a next step, we will optimize the motor´s design, characterize their performance and reliability, and use the stepper motors to power a micropositioning device in iMRI-phantom tests.

Research on fuzzy PID lower extremity exoskeleton control system based on pneumatic drive

The lower extremity rehabilitation exoskeleton based on pneumatic muscle actuator was introduced. The gait experiments were implemented, and the biomechanics of human walking were outputted for the design and control of lower rehabilitation exoskeleton. The experiment platform was built based on DSPACE system and the fuzzy adaptive PID controller was applied for the control of lower rehabilitation exoskeleton. The experiment results showed that adding the pre-feedback control based on fuzzy adaptive PID can significantly reduce the time that the system, and the experiment of swing control also showed that a high level of coordination between the user swing motion and the exoskeleton leg.

DESIGN, FABRICATION AND TESTING OF PNEUMATIC MUSCLE ACTUATOR FOR ARTIFICIAL HUMAN ARM

This paper provides detailed design and characterisation of the Pneumatic Muscle Actuator (PMA) proposed for actuating an artificial human arm. The anatomy and the load carrying capacity of the human arm are considered for designing the PMA. The PMA is fabricated using the braided sleeve and latex tubes, and a pneumatic circuit is designed for its characterisation. The proposed artificial human arm with PMA can be used as a teaching aid to simulate neurological disorders.

Development of New Soft Wearable Balance Exercise Device Using Pneumatic Gel Muscles

Decreased ability to control posture is correlated with the risk of falls among older individuals. In particular, reactive postural control ability response to even small perturbations is important for fall prevention of older individuals. The current study sought to design a new wearable assistive device for improving balance function by generating small perturbations using pneumatic gel muscle (PGM). Furthermore, we investigated the effects of using the proposed device for balance training. The proposed wearable balance exercise device utilized PGMs possessing various features, such as a lightweight design and the ability to generate small perturbations with a small power source. We investigated the effects of the device on reactive postural control exercises. Seven healthy participants participated in this study. Three-dimensional acceleration data (Ax, Ay, and Az) were measured from participants during a single leg stance in each session. The peak Ax value generated by perturbations and responses significantly differed from baseline peak acceleration. The peak Ay value caused by perturbations was significantly decreased compared with baseline peak acceleration. In addition, the root mean square Ax value of the post-test significantly decreased compared with the pre-test value. Our results revealed that the proposed wearable balance exercise device was able to create small perturbations for assessing reactive postural balance control. Furthermore, the device was able to improve users’ stability.

Parallel Compliance Design for Increasing Robustness and Efficiency in Legged Locomotion—Proof of Concept

Benefiting from serial compliance in series elastic actuators can be considered as a breakthrough in robotics. Recently, applying the parallel compliance in robot designs is growing based on its advantages such as reduction in consumed torques. In this paper, we aim at employing parallel compliance to increase walking robustness of bipedal robots against model uncertainties. Utilizing passive compliant elements instead of adapting the controller in order to cope with uncertainties makes the system more efficient and less sensitive to measurement issues such as delays and noise. We introduce a methodology for designing both parallel compliance and controller using hybrid zero dynamics concept. This study includes simulation results representing the design approach and preliminary experiments on parallel compliance effects on efficiency of a robot joint position control. The simulations comprise a compass gait (2-link) model and a 5-link model. The ground slope and robot segment lengths are considered as uncertain parameters in the first and second models, respectively. The control target is met by the insertion of compliant structures parallel to the actuators. In order to employ the proposed method on a real robot, we suggest using pneumatic air muscles as parallel compliant elements. Pilot experiments on the knee joint of BioBiped3 robot support the feasibility of suggested method.

Effects of wearable power assist device on low back fatigue during repetitive lifting tasks

BackgroundA wearable power assist device was developed to reduce the stress on the lower back by using pneumatic muscles. The purpose of this study was to explore whether the assist device could reduce the activity or fatigue of lower back muscles during a repetitive lifting task. MethodsTwelve male subjects participated in the study. Electromyography of the thoracic erector spinae at the T9 level and lumbar erector spinae at the L3 level was recorded during 90 lifts in 15 min. Subjects' heart rate and Borg's Rate of Perceived Exertion Scale score were recorded during lifting sessions. FindingsThe electromyography amplitude of thoracic erector spinae and lumbar erector spinae was only increased by 32.45% and 40.17%, respectively, when the wearable power assist device was used when comparing the pre- and post-lifting task. Whereas it was increased by 125.78% and 85.90%, respectively, when the wearable power assist device was not used. The decrease in electromyography median frequency from the start until the end of the lifting session was significantly lower when wearing the assist device for the thoracic erector spinae (2.72% vs 7.45%) and the lumbar erector spinae (3.91% vs 13.70%). Use of the assist device also significantly reduced the percentage change in heart rate and Borg Scale (p < 0.05). InterpretationThe use of the wearable power assist device showed less back muscle contraction compared to the no-use, which can potentially minimize the level of back muscle fatigue across the lifting session.

Using the Bioelectric Signals to Control of Wearable Orthosis of the Elbow Joint with Bi-Muscular Pneumatic Servo-Drive

SUMMARYThis study presents a new design of a wearable orthosis of elbow joint with a bimuscular pneumatic servo-drive (PSD) with control based on the recording of bioelectric signals (BESs). The authors analyzed the impact of the induced brain activity and the muscular tension within the head of the participant on the BESs that can be used to control the PSD of the elbow joint orthosis. To control the elbow joint orthosis, a distributed control system (DCS) was developed, which contains two control layers: a master layer connected to the device for recording the BES and a direct layer contained in a wireless manner with the controller of the PSD. A kinematic-dynamic model of the elbow joint orthosis, patterned after the biological model of human biceps–triceps, was used in the programming of the PSD controller. A biomimetic dynamic model of the pneumatic muscle actuator (PMA) was used, in which the contraction force results from the adopted exponential static model of the pneumatic muscle (PM). The use of direct visual feedback (DVF) makes it possible for the participant to focus on the movement of the orthosis taking into account the motoric functions of the elbow.

Adjustable compliance soft gripper system

This article proposes a novel, innovative, soft gripper system developed for the manipulation of objects of unknown or unspecified shape and consistence. This could be achieved by the utilization of a linear pneumatic muscle benefitting from an inherently compliant behaviour. A gripper system of this type does not require the presence of sensors or complex controllers, as it is the mechanical system itself that provides the required adaptive behaviour. The compliance of the system is ensured by the variations of the air pressure fed to the pneumatic muscle, monitored and controlled in a closed loop by means of proportional pressure regulator.

Comparison of Control Techniques in a Weight Lifting Exoskeleton

The back pain is the most common injury in human activities where heavy objects must be lifted or must be suspended for a long time. A weight lifting exoskeleton also known as force augmentation exoskeleton is designed to reduce the strain on the back and the limbs and reduce the risk to suffer injuries. On the other hand, different kinds of controllers have been implemented to achieve whit this goal, for example, a conventional PD Control, PD Control with Gravity Compensation, PD Control with Adaptive Desired Gravity Compensation and PD Control with Robust Compensator. This paper aims to evaluate and compare the performance from the previously cited controllers used to reduce the strain in the back, through the implementation of each controller in a three Degrees Of Freedom (DOF) exoskeleton powered by pneumatic muscle actuators; some numerical simulations as well as experimental trials have been conducted and three different performance indices were used in order to determine the effectiveness of each one with respect to the simple PD controller when the mass to be lifted is unknown.

An Echo State Gaussian Process-Based Nonlinear Model Predictive Control for Pneumatic Muscle Actuators

Pneumatic muscle actuators (PMAs), a kind of soft/compliant actuators, have been attracted a great deal of attention in the studies of rehabilitation robots. However, the nonlinearities, uncertainties, hysteresis, and time-varying features of PMAs bring a lot of difficulties in their high-precision trajectory tracking tasks. In this paper, an echo state Gaussian process-based nonlinear model predictive control (ESGP-NMPC) is designed for the PMAs. The proposed strategy is comprised of an ESGP, which is suitable for modeling unknown nonlinear systems as well as measuring their uncertainties, and a gradient descent optimization algorithm for calculating the control signal sequences. Based on the Lyapunov theorem, characteristics of the closed-loop system are analyzed to guarantee the asymptotical stability. Both simulations and physical experiments are carried out to illustrate the validity of the proposed control strategy. Compared with other conventional methods, the ESGP-NMPC can achieve a better model fitting for the PMA and control performance for the high-precision tracking tasks. Note to Practitioners —High-precision control of pneumatic muscle actuators (PMAs) is a vital problem when PMAs are utilized as actuators of rehabilitation robots since the patient’s safety and the performance of rehabilitation tasks are largely dependent on the accuracy of the actuators. Conventional model-based control approaches usually require relatively accurate identification of system parameters, which is difficult for the PMA, owing to its strong nonlinear and time-varying characteristics. This paper proposes a new model predictive control method based on an echo state Gaussian process that can describe the unknown dynamics of a PMA due to its universal approximation property. Through the optimization method, the controller can be efficiently realized and presents better performances than some comparatives. By applying this approach, it is possible to achieve not only high-precision control of PMAs but also a certain degree of robustness to the load.

Mathematical modeling of changes in geometric parameters of pneumatic muscles

Today, this type of drive as pneumatic muscles has wide application. Pneumatic muscle is a one-way drive and has such advantages as the developed force, as well as speed. Pneumatic muscles, compared to pneumatic cylinders, have a non-linear structure that needs to be correctly identified. In this paper, we study the dynamic processes of pressure change in the working cavity of a pneumatic muscle in order to build a mathematical model, which can later be used to develop control systems, where the main actuator is pneumatic muscle, as well as to accurately describe and predict the geometric parameters of pneumatic muscles on pressure of compressed air in the working cavity.

Angle Tracking Adaptive Backstepping Control for a Mechanism of Pneumatic Muscle Actuators via an AESO

This paper presents an adaptive backstepping controller for a mechanism of pneumatic muscle actuators via an adaptive extended state observer. A dynamic model of the mechanism is established with two unknown parameters estimated by using adaptive laws. An adaptive extended state observer is established to estimate total disturbances and states of the mechanism. Moreover, adaptive extended state observer gains are obtained by adaptive laws and parallel D-eigenvalues, whose time-varying multiplier $n$ th-order derivatives are derived by tracking differentiators. Finally, a nonlinear adaptive backstepping controller is designed and the effectiveness of the proposed method is expressed by experimental results.

A Sampled-Data Approach to Nonlinear ESO-Based Active Disturbance Rejection Control for Pneumatic Muscle Actuator Systems with Actuator Saturations

In this paper, an active disturbance rejection control scheme with a nonlinear sampled-data extended state observer (NSESO) is proposed for a pneumatic muscle actuator (PMA) system. The phenomenon of the actuator saturation is taken into account in the design procedure. The NSESO is utilized to estimate the so-called total disturbance that reflects the aggregated impacts of unmodeled nonlinearities and disturbances. Then, an NSESO-based composite control strategy is designed, where the estimates provided by the designed NSESO serve as the compensation to eliminate the total disturbance. Finally, a number of practical experiments on the PMA systems are conducted to verify the validity and applicability of the proposed design method.

Eco-friendly innovation gripping systems actuated by pneumatic muscles

The paper focuses on the development of innovative, bionic, eco-friendly and light gripping systems. Within this broader context the paper presents and discusses four innovative constructive solutions for a gripping system mountable on an industrial robot, based on actuation by a linear pneumatic muscle and transmission of motion by gear and rack mechanism. The method underlying the development of these novel

Optimizing Control of Passive Gait Training Exoskeleton Driven by Pneumatic Muscles Using Switch-Mode Firefly Algorithm

SummaryThis paper presents a lower-limb exoskeleton that is actuated by pneumatic muscle actuators (PMAs). This exoskeleton system is composed of the mechanical structures, a treadmill, and a weight support system. With the cooperative work of the three parts, the system aims to assist either the elderly for muscle strengthening by conducting walking activities or the stroke patients during a rehabilitation training program. A mechanism is developed to separate the PMAs from the wearer’s legs to reduce the subject’s physical exertion. Furthermore, considering the difficulty in the modeling of proposed PMAs-driven exoskeleton, a safe and model-free control strategy called proxy-based sliding mode control (PSMC) is used to ensure proper control of the exoskeleton. However, the favorable performances are strongly dependent on the appropriate control parameters, which may be difficult to obtain with blind tuning. Therefore, we propose a global parameters optimization algorithm called switch-mode firefly algorithm (SMFA) to automatically calculate the pre-defined object function and attain the most applicable parameters. Experimental studies are conducted, and the results show the effectiveness of the proposed method.

An Extended Proxy-Based Sliding Mode Control of Pneumatic Muscle Actuators

To solve the problem of controlling an intrinsically compliant actuator, pneumatic muscle actuator (PMA), this paper presents an extended proxy-based sliding mode control (EPSMC) strategy. It is well known that the chattering phenomenon of conventional sliding mode control (SMC) can be effectively solved by introducing a proxy between the physical object and desired position, which results in the so-called proxy-based sliding mode control (PSMC). To facilitate the theoretical analysis of PSMC and obtain a more general form of controller, a new virtual coupling and a SMC are used in our proposed EPSMC. For a class of second-order nonlinear system, the sufficient conditions ensuring the stability and passivity are obtained by using the Lyapunov functional method. Experiments on a real-time PMA control platform validate the effectiveness of the proposed method, and comparison studies also show the superiority of EPSMC over the conventional SMC, PSMC, and PID controllers.

Long-range snake-like robot powered by pneumatic McKibben muscles

Long-range snake-like robot powered by pneumatic McKibben muscles