• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.33 no.10
• /
• pp.1081-1086
• /
• 2009

This paper presents dynamic characteristics of pneumatic artificial muscles. Since the actuating performance of a pneumatic muscle is closely related to the input pressure of a pneumatic muscle, the air flow model on a valve orifice and an elastic bladder of the muscle is formulated to estimate precisely the pressure variance of pneumatic muscles during deflating and inflating process. Frequency response experiments are performed with an antagonistic system consisting of two pneumatic muscles and fast pneumatic control valves. Comparing with experimental results, the proposed model yielded good performance in estimating dynamic motions of the antagonistic system as well as the pressure variance of the pneumatic artificial muscles

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.76-81
• /
• 2004

Problems with the control, oscillatory motion and compliance of pneumatic systems have prevented their widespread use in advanced robotics. However, their compactness, power/weight ratio, ease of maintenance and inherent safety are factors that could be potentially exploited in sophisticated dexterous manipulator designs. These advantages have led to the development of novel actuators such as the McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle Manipulators. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external inertia load in the pneumatic artificial muscle manipulator. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is newly proposed. This estimates the external inertia load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external inertia loads.

• Journal of Mechanical Science and Technology
• /
• v.18 no.8
• /
• pp.1388-1400
• /
• 2004

Problems with the control, oscillatory motion and compliance of pneumatic systems have prevented their widespread use in advanced robotics. However, their compactness, power/weight ratio, ease of maintenance and inherent safety are factors that could be potentially exploited in sophisticated dexterous manipulator designs. These advantages have led to the development of novel actuators such as the McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle Manipulators. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external inertia load in the pneumatic artificial muscle manipulator. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is newly proposed. This estimates the external inertia load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external inertia loads.

• Journal of Power System Engineering
• /
• v.10 no.3
• /
• pp.97-103
• /
• 2006

In this study, a position trajectory tracking control algorithm is proposed for a pneumatic artificial muscle driving apparatus composed of a actuator which imitates the muscle of human, a position sensor and a control valve. The controller applied to the driving apparatus is composed of a state feedback controller and disturbance observer. The feedback controller which feeds back position, velocity and acceleration is derived from the linear model of pneumatic artificial muscle driving apparatus. The disturbance observer is designed to improve trajectory tracking performance and to reduce the effect of model discrepancy. The effectiveness of the designed controller is proved by experiments and the experimental results show that the pneumatic artificial muscle driving apparatus with the proposed control algorithm tracks given position reference inputs accurately.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.4
• /
• pp.82-90
• /
• 2009

Pneumatic cylinder is one of the low cost actuation sources which have been applied in industrial and prosthetic application since it has a high power/weight ratio, a high-tension force and a long durability However, the control problems of pneumatic systems, oscillatory motion and compliance, have prevented their widespread use in advanced robotics. To overcome these shortcomings, a number of newer pneumatic actuators have been developed such as McKibben Muscle, Rubber Actuator and Pneumatic Artificial Muscle (PAM) Manipulators. In this paper, one solution for position control of a robot arm, which is driven by two pneumatic artificial muscles, is presented. However, some limitations still exist, such as a deterioration of the performance of transient response due to the changes in the external load of the robot arm. To overcome this problem, a switching algorithm of the control parameter using a learning vector quantization neural network (LVQNN) is proposed in this paper. This estimates the external load of the pneumatic artificial muscle manipulator. The effectiveness of the proposed control algorithm is demonstrated through experiments with different external working loads.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.30 no.6 s.249
• /
• pp.662-669
• /
• 2006

The pneumatic muscle actuator consists of an air bellows tube with two end-flanges. The air bellows tube is made from rubber layers and flexible sheathing formed from nylon 6 fibers. This structure can be stretched or compressed to convert the radial expansive forces into contractile forces. We performed the finite element analysis and the performance test of pneumatic muscle actuator. Also, the pneumatic muscle actuator was manufactured and tested by home-made tester. The results of FEA was similar with performance test below the maximum error of 42 %.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.5
• /
• pp.100-107
• /
• 1997

A pneumatic artificial muscle type of actuator, which acts similar to human muscle, is developed recently. In this paper, an adaptive controller is presented for the trajectory tracking problem of a two-degree- of-freedom manipulator using two pairs of pneumatic artificial muscle actuators. Due to the nonlinearity and the uncertainty on the dynamics of the actuator, it is difficult to make the effective control schemes of this system. By the adaptive control law which inclueds a nonlinear "feedforward" term compensating paramet- ric uncertainties in addition to P.I.D. scheme, both golbal stability of the system and convergence of the tracking error are guaranted. The effectiveness of the proposed control method for the manipulator using this actuator is illustrated through experiments.periments.

• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.1566-1571
• /
• 2003

PGO(Powered Gait Orthosis) mounted with pneumatic muscle as an actuator is upgraded model from RGO(Replicate Gait Orthosis) for paraplegia patients to walk easy and safe. Pneumatic muscles supply powers to both hip joint during PGO gait. The objective of this research is to develop the PGO gait simulation model. Dynamic model of PGO linkage system is processed. Mathematical model of pneumatic muscle was developed and combined it with PGO linkage system. Developed simulation model will be used as a tool for evaluation of the efficiency of pneumatic muscle and for analysis the PGO system.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.20 no.6
• /
• pp.1882-1892
• /
• 1996

This paper is concerned with the position control of the ond degree-of freedom manipulator using pneumatic artificial muscle actuator which is built to have a proper compliance. For t his pneumatic artificial muscle actuator though, it is difficult to make an effective control scheme due to the nonlinearity and uncertainties on the dynamics of the actuator. In this paper, a third-order equation of motion is derived for the actuator including the dynamics of the pneumatic servovalve. Later, various modeling uncertainties due to the nonlinearity and unmodeled dynamics of the servo vlave and the actuator are taken care of, as a trade-off between the closed-loop performance of the controlled system and its robustness to uncertainties. A controller using .mu. synthesis thchnique is designed, and robust performance against measurement noise, various modeling uncertainties due to the dynamics of the servo valve and actuator is achieved. The effectiveness of the proposed control methods is illustrated through simulations and experiments.

• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.11
• /
• pp.1217-1224
• /
• 2013

In this paper, a hand exoskeleton actuated by air muscles(soft hand exoskeleton) is introduced. Some soft hand exoskeletons have already been developed to overcome the defects of hand exoskeletons based on linkage and pneumatic piston system-they are usually bulky and do not have enough degree of freedom(DOF). However, soft hand exoskeletons still have defects. Their motions are not precise as linkage based hand exoskeletons, because their actuator, such as air muscle is made of soft materials. So we developed a new linkage which is not bulky and has redundant DOF. It is combined with air muscle in a specific way so that it acts as a guide when air muscle is actuated. Some experiments were conducted to evaluate the validity and usability of our hand exoskeleton.