• The Journal of Korea Robotics Society
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• v.19 no.3
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• pp.274-280
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• 2024

With the recent emergence of collaborative robots, demand for grippers to be used in service sites is increasing. Soft grippers have advantages in terms of compliance, cost, weight, and stability, but it is difficult to handle objects of various shapes, sizes, and weights with a single gripper. In this study, based on a fluidic elastomer actuator (FEA), we propose a pneumatic soft gripper that can grip a variety of objects, consisting of fingers capable of both grasping and vacuum suction and a base with variable stroke between the fingers using a pneumatic cylinder. A check valve is installed inside the finger, so that when positive pressure is supplied, the finger expands to perform adaptive grasping, and when negative pressure is supplied, vacuum suction can be performed. Grasping experiments were conducted on various objects to evaluate the performance of the proposed gripper, and 94% of 54 gripping objects were successfully grasped.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.4
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• pp.63-68
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• 2006

This research presents the reliability analysis of the pneumatic actuator within the tape feeder that is used to transfer the correct force to linked parts during l.0E+7 cycles. First, the degradation analysis for thrust and air leakage is executed to obtain the failure data of a product based on its performance over time. Second, once the parameters has been calculated using the weibull 2-parameter distribution and MLE(Maximum Likelihood Estimation), information related to life such as reliability, failure rate, probability density function is estimated. Finally, MTTF(Mean Time To Failure) and $B_{10}$ life of actuators are calculated. MTTF means the mean life at the confidence level and $B_{10}$ life refers to the time by which 10% of the product would fail. In this study, failure causes and solutions are examined using the reliability analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.93-94
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• 2007

• The Journal of Korea Robotics Society
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• v.16 no.1
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• pp.23-28
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• 2021

The gripper with a soft pneumatic actuator uses a soft material, unlike the gripper that uses a rigid body, so it is safer and lighter to interact with objects without advanced control technology. Among the soft pneumatic actuators that have been studied, PneuNets actuators have bellows shape, which enable quick operation and complete bending with only small material deformation at low pressure. In this study, we suggested improved form of PneuNets actuators to obtain the performance of the soft actuator that a larger bending angle and larger bending force at a small pressure. An experiment was designed and conducted to measure the bending angle and bending force according to the pressure. As a result, it was confirmed through experiments that the improved model has a maximum bending angle at a pressure of 5 kPa lower than that of the previous model, and a maximum bending force of 1.97 times at the same pressure.

• 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.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1210-1214
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• 2008

Electro-pneumatic servo valve is an electro-mechanical device which converts electric signal into pneumatic flow rate or pressure. In order to improve the overall performance of pneumatic servo systems, electro-pneumatic servo valves are required, which have fast dynamic characteristic, no air leakage at null, and can be fabricated at a low-cost. The first objective of this research is to design and fabricate a new electro-pneumatic servo valve which satisfies the above-mentioned requirements. In this paper, we has been modeled as a system consisting of coupled electro-mechanic and mechanical subsystems. The appropriateness of the model has been verified by simulation. The simulation model resolves the valve body motion and the solenoid current at high accuracy. Also, we are calculate the displacement of spool and computed results show winding currents, magnetic actuator force, flux density line, displacement, velocity, back EMF, eddy current etc.

• Journal of the Korean Society of Industry Convergence
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• v.11 no.4
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• pp.209-216
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• 2008

The ball screw position control system driven by a pneumatic motor using continuous sliding mode is proposed. The design and performance of proposed servo system are presented by means of examples tested under practical service conditions. Results of experimental implementation on the proposed system illustrate the effectiveness of the ball screw position control system driven by a pneumatic motor using continuous sliding mode as a servo pneumatic actuator driven by a pneumatic motor.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.103-108
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• 2005

Loading/Unloading task in the real industry is performed by crane, but most of the loading/unloading task with the weight of 5kg∼30kg is done by human workers and this kind of work causes industrial disaster of workers. Therefore it is necessary to develop low cost loading/unloading manipulator system to prevent this kind of industrial accidents. This paper is concerned with the design and fabrication of 2 axis pneumatic manipulators using on/off solenoid valves and accurate position control without respect to the external load and low damping in the pneumatic rotary actuator. To overcome the change of external load, switching of control parameter using LVQNN (Learning Vector Quantization Neural Network) is newly applied, which estimates the external loads in the pneumatic cylinder. As an underlying controller, a state feedback controller using position, velocity and acceleration is applied to the switching control system. The effectiveness of the proposed control algorithms are demonstrated through experiments of pneumatic cylinder with various loads.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.530-535
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• 2002

Pneumatic control system has been applied to build many industrial automation systems. But most of them are sequence control type because of their low costs, safety, reliability, etc. Pneumatic servo system is rarely applied to real industrial fields because accurate position control is very difficult due to its nonlinearity and compressibility of air. In pneumatic servo control system, a pneumatic servo valve can be applied, But it is very expensive and has no advantage of low cost compared with a common pneumatic system. This paper is concerned with the accurate position control of a rodless pneumatic cylinder using on/off solenoid valve. A novel Intelligent Modified Pulse Width Modulation(MPWM) is newly proposed. The control performance of this pneumatic cylinder depends on the external loads. To overcome this problem, switching of control parameter using artificial neural network is newly proposed, which estimates external loads on rodless pneumatic cylinder using this training neural network. As an underlying controller, a state feedback controller using position, velocity and acceleration is applied in the switching control the system. The effectiveness of the proposed control algorithms are demonstrated through experiments nth various loads.