• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.127-134
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• 1995

For use in patients with severe forms of heart disease for which no surgical repair is possible, development of artificial hearts has many importance in point of economics, medical and industrial applications. To provide a sufficient cardiac output to the physiological demands of circulatory systems is the objective of control systems for an electromechanical artificial heart, which is based on the stable controller design for the motor in the artificial heart. In this paper, an implantable microcontroller-based brushless DC motor control system with the implantability, reliability, and stability is introduced. The developed control system for the artificial heart has the following advantages: (1) It is possible to be implanted in a body by realizing the fundamental functions such as a motor speed detection, proportional-intergral control, timer, and PWM generation through a software programming. (2) Thus, the power consumed in the controller is reduced. (3) The reliability and stability are improved through the reduction of electronic parts and line connetions at the controller. The performance of the artificial hearts and control system developed was evaluated through a series of mock circulatory experiments and a reliability test for one and half years. A sheep with the artificial heart and control system was survived for three days.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.88.2-88
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• 2001

In this paper Author introduce a new field named Artificial Life and its main directions of research. That is the research of evolutionary robot and artificial brain. Then author explored the advanced scientific thought hidden in them. Furthermore, the author tries intuitively to show a new type of control that is heuristically raised from artificial life research. It could be named as evolutionary control. This type of control is more like human body´s structure, and it is self-organized.

• 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.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.200-209
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• 1999

This paper presents a precise tracking control scheme for the proposed parallel robot using artificial neural network. This control scheme is composed of three feedback controllers and one feedforward controller. Conventional PD controller and artificial neural network are used as feedback and feedforward controller respectively. A backpropagation learning strategy is applied to the training of artificial neural network, and PD controller outputs are used as target outputs. The PD controllers are designed at the robot dynamics based on inter-relationship between active joints and moving platform. Feedback controllers insure the total stability of system, and feedforward controller generates the control signal for trajectory tracking. The precise tracking performance of proposed control scheme is proved by computer simulation.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.564-570
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• 2005

This paper provides a basis for investigating 'The Origin of Artificial Species,' as a robot can be considered as an artificial creature. To design an artificial creature, its general internal architecture is presented and its artificial chromosomes are proposed as its essential components. Rity as an artificial creature is developed in a virtual world of PC to test the world's first robotic 'chromosomes,' which are a set of computerized DNA (Deoxyribonucleic acid) codes for creating robots (artificial creatures) that can have their own personality, and can ultimately reproduce their kind, or even evolve as a distinct species. The effectiveness of the artificial chromosomes is demonstrated by implanting the genetic code into two Ritys living in a virtual world, in order to define their personality.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1704-1707
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• 1997

In this work, position and vibratiion control of a two-link manipulator with one flexible link, which an unkoun but bounded payload mass and two pair of artificial muscle-type penumatic actuators, are investgated. A flexible link robot has advantages over a figid link robot in the sense that it is much safer when it cones into contact with its environment, including humans. Furthermore, for the sake of safety, it would be more desirabel if an actuator could deliver required force while maintaining proper compliance. An artificial muscle-type penumatic actuator is adequate for such cases. In this study, a controller based on singular perturbation method, adaptive and sliding mode contro, and .mu.-synthesis is developed. The effectiveness of the proposed control scheme is confirmed through simulations and experiments.

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