• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1697-1700
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• 2003

We propose a new technique for real-time controller design of a autonomous cruise mobile robot with three drive wheels. The proposed control scheme uses a Gaussian function as a unit function in the fuzzy neural network, and a 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 control performance of the proposed controller is illustrated by performing the computer simulation for trajectory tracking of the speed and azimuth of a autonomous cruise mobile robot driven by three independent wheels.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.312-318
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• 2003

We propose a new technique for the cruise control system design of a mobile robot with three 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 teaming architecture. It is proposed a learning controller consisting of too 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 three independent wheels.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.2
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• pp.18-28
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• 2001

Super computers has been utilized to carry out vehicle dynamics in real time. This research propose an implicit integra-tion method for vehicle state variables. Newton chord method is empolyed to solve the equations of motion and con-straints. The equations of motion and constraints are formulated such that the Jacobian matrix for Newton chord method is needed to be computed only once for a dynamic analysis. Numerical experiments showed that the Jacobian matrix generat-ed at the initial time could have been utilized for the Newton chord iterations throughout simulations under various driving conditions. Convergence analysis of Newton chord method with the proposed Jacobian updating method is carried out. The proposed algorithm yielded accurate solutions for a prototype vehicle multibody model in realtime on a 400 MHz PC compatible.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.171-176
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• 2010

Railway has recently played an important role in preventing global warming caused by green house gases and furthering a low carbon green growth, The various railway research centers have conducted facilitated studies on saving energy. In particular, urban railway has emerged as the best means of public transportation in terms of punctuality, safety and environmentally friendliness. There are various ways to save energy in terms of operation of urban railway system, and they can be generally divided into hardware aspects that pertain to structure of vehicles and development of control system and software aspects that pertain to effective operation of trains based on operation patterns and diagram control. In this paper, we investigated drive assistance system for railway energy efficiency. The railway operation patterns and train diagram management programs were researched.

• Aerospace Engineering and Technology
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• v.6 no.2
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• pp.236-244
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• 2007

The 40% scaled vehicle of Smart UAV has been developed for the investigation of basic flight characteristics and the verification of flight control algorithm. The similar gimbal hub and drive train with the full scale UAV were implemented and a forced air cooling reciprocating engine was installed. The various kind of tests were conducted for the major components of the vehicle. The important performance and mechanical endurance of the fabricated vehicle were identified by ground and hovering test.

• 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 KIPE Conference
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• 2006.06a
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• pp.4-6
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• 2006

본 연구에서는 열차 추진 장치 시스템에 엔진의 중심부를 모의할 수 있는 Simplorer의 프로그램을 개발하여 M-G Set으로 모사한다. 열차의 엔진부와 발전기 구동에서의 제어는 DTC(Direct Torque Control) 제어로 모사 하였다. M-G Set을 구성은 견인력 토크지령을 받아 엔진부에서 DTC제어를 하였고, 발전기 구동 부는 속도지령을 받는 DTC제어로 하여 추진 장치 성능시험설비 열차운행모의에 의한 전력 조류 해석, 소비 및 회생전력을 분석할 수 있도록 하였다.

• 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.