• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.250-254
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• 2001

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.6
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• pp.731-737
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• 1999

This paper describes the path tracking control for a mobile robot which has two casters at the front and rear to keep balance and two driving wheels on the left and right sides of its body. Power wheeled steering method is adapted to control heading of the robot. It is very difficult to find appropriate feedback gains when linear regulator control scheme is adapted to path tracking con-trol of this type of robot. Therefore in this paper we propose the path tracking control algorithm using the fuzzy logic control scheme for this type of root. Simulation to prove the validity of the proposed two algorithms is performed. The results are reported as last part in this paper.

• Journal of Ocean Engineering and Technology
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• v.11 no.1
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• pp.84-95
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• 1997

This paper presents a new approach to the design speed and azimuth control of a mobile robot with drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the frmework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simple the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.199-203
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• 2000

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.207-212
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• 2004

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.130-134
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• 2000

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• The Journal of Korea Robotics Society
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• v.5 no.3
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• pp.177-185
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• 2010

In this paper, a wall climbing robot, called LAVAR, is developed, which is using an impeller for adhering. The adhesion mechanism of the robot consists of an impeller and two-layered suction seals which provide sufficient adhesion force for the robot body on the non smooth vertical wall and horizontal ceiling. The robot uses two driving-wheels and one ball-caster to maneuver the wall surface. A suspension mechanism is also used to overcome the obstacles on the wall surface. For its design, the whole adhering mechanism is analyzed and the control system is built up based on this analysis. The performances of the robot are experimentally verified on the vertical and horizontal flat surfaces.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.235-240
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• 2002

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and back propagation algorithm to train the fuzzy neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.69.3-69
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• 2001

This paper presents a new approach to the design of cruise control system of a mobile robot with two drive wheel. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the framework of the specialized learning architecture. It is proposed a learning controller consisting of two neural network-fuzzy based on independent reasoning and a connection net with fixed weights to simply the neural networks-fuzzy. The performance of the proposed controller is shown by performing the computer simulation for trajectory tracking of the speed and azimuth of a mobile robot driven by two independent wheels.

• Journal of Korean Vacuum Science & Technology
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• v.6 no.2
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• pp.62-66
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• 2002

Hydraulic pumps are used to control the landing wheels of aircrafts, and their proper operation is vital to plane safety It is well hewn that adhesive wear failure is a major cause of pump failure. A dual nitrogen plasma immersion ion implantation process calling for the implantation of nitrogen at two different energies and doses has been developed to enhance the surface properties of the disks in the pumps. The procedures meet the strict temperature requirement of <200$^{\circ}C$, and after the treatment, the working lifetime of the pumps increases by more than a factor of two. This experimental protocol has been adopted by the hydraulic pump factory as a standard manufacturing procedure.