• Journal of the Korean Society for Precision Engineering
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• v.12 no.1
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• pp.97-103
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• 1995

This paper describes position and force hybrid control for a robot manipulator with artificial rubber muscle actuators. The controller using two control laws such as PID control and fuzzy logic control methods is designed. This paper concludes to show the effectiveness of the proposed controller by some experiments for a two-link manipulator.

• Smart Structures and Systems
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• v.16 no.3
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• pp.479-496
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• 2015

In this work, a novel artificial circular muscle based on shape memory alloy (S.M.A.) is proposed. The design is inspired from the natural circular muscles found in certain organs of the human body such as the small intestine. The heating of the prestrained SMA artificial muscle will induce its contraction. In order to measure the mechanical work provided in this case, the muscle will be mounted on a silicone rubber cylindrical tube prior to heating. After cooling, the reaction of the rubber tube will involve the return of the muscle to its prestrained state. A finite element model of the new SMA artificial muscle was built using the software "ABAQUS". The SMA thermomechanical behavior law was implemented using the user subroutine "UMAT". The numerical results of the finite element analysis of the SMA muscle are presented to shown that the proposed design is able to mimic the behavior of a natural circular muscle.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.76-81
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• 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
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• v.18 no.8
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• pp.1388-1400
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• 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.3
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• pp.485-492
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• 1994

Trajectory tracking control porblems are described for a two-link robot manipulator with artificial rubber muscle actuators. Under the assumption that the so-called independent joint control is applied to the control system, the dynamic model for each link is identified as a linear second-order system with time-lag by the step response. Two control laws such as the feedforward and the computed torque control methods, are experimentally applied for controlling the circular trajectory of an actual robot mainpulator.

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

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.642-646
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• 1992

Trajectory tracking control problems are described for a two-link robot manipulator with artificial rubber muscle actuators. Under the assumption that the so-called independent joint control is applied to the control system, the dynamic model for each link is identified as a linear second-order system with time-lag by the step response. Two control laws such as the feedforward and the computed torque control methods, are experimentally applied for controlling the circular trajectory of an actual robot manipulator.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1983-1989
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• 2005

Industrial robots are powerful, extremely accurate multi-jointed systems, but they are heavy and highly rigid because of their mechanical structure and motorization. Therefore, sharing the robot working space with its environment is problematic. A novel pneumatic artificial muscle actuator (PAM actuator) has been regarded during the recent decades as an interesting alternative to hydraulic and electric actuators. Its main advantages are high strength and high power/weight ratio, low cost, compactness, ease of maintenance, cleanliness, readily available and cheap power source, inherent safety and mobility assistance to humans performing tasks. The PAM is undoubtedly the most promising artificial muscle for the actuation of new types of industrial robots such as Rubber Actuator and PAM manipulators. However, some limitations still exist, such as the air compressibility and the lack of damping ability of the actuator bring the dynamic delay of the pressure response and cause the oscillatory motion. In addition, the nonlinearities in the PAM manipulator still limit the controllability. Therefore, it is not easy to realize motion with high accuracy and high speed and with respect to various external inertia loads in order to realize a human-friendly therapy robot To overcome these problems a novel controller, which harmonizes a phase plane switching control method with conventional PID controller and the adaptabilities of neural network, is newly proposed. In order to realize satisfactory control performance a variable damper - Magneto-Rheological Brake (MRB) is equipped to the joint of the manipulator. Superb mixture of conventional PID controller and a phase plane switching control using neural network brings us a novel controller. This proposed controller is appropriate for a kind of plants with nonlinearity uncertainties and disturbances. The experiments were carried out in practical PAM manipulator and the effectiveness of the proposed control algorithm was demonstrated through experiments, which had proved that the stability of the manipulator can be improved greatly in a high gain control by using MRB with phase plane switching control using neural network and without regard for the changes of external inertia loads.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.443-444
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• 2006

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.725-728
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• 2008

An elbow orthosis with a pneumatic rubber actuator has been developed to assist and enhance upper limbs movements and has been examined for the effectiveness. The effectiveness of the elbow orthosis was examined by comparing muscular activities during alternate dumbbell curl motion wearing and not wearing the orthosis. The subjects participated in the experiment were younger adults in their twenties. The subjects were instructed to perform dumbbell curl motion in a sitting position wearing and not wearing orthosis in turn and a dynamometer was used to measure elbow joint torque outputs in an isokinetic mode. Orthosis was controlled using contractile muscle force that is measured from force sensor through cDAQ-9172 board. The air pressure of the pneumatic actuator was 0.3MPa the most suitable air pressure. For the analysis of muscular activities, Electromyography of the subjects was measured during alternate dumbbell curl motion. The experiment results showed that the muscular activities wearing the elbow orthosis were reduced. With this, we confirmed the effectiveness of the developed elbow orthosis.