• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.1
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• pp.71-77
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• 2007

Dangerous driving is a major cause of traffic accidents in Korea. It becomes more serious for commercial vehicles due to higher fatality rates. The Safe Driving Management System (SDMS), developed in this research, is a comprehensive solution that monitors and stores driving conditions of vehicles, detects dangerous driving situations, and analyzes the results in real time. The Safe Driving Management System consists of a vehicle movement information controller, a dangerous driving detection algorithm and a vehicle movement data report and analysis program. The dangerous driving detection algorithm detects and classifies dangerous driving conditions into representative cases such as sudden acceleration, sudden braking, sudden lane change, and sudden turning. Both computer simulation and vehicle test have been conducted to develop and verify the algorithm. The Safe Driving Management System has been implemented on commercial buses to verify its reliability and objectivity. It is expected that the system can contribute to prevention of traffic accidents, systemization of safe driving management and reduction of commercial vehicle operation costs.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.2
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• pp.865-874
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• 2019

A controller for an underwater glider is presented. Considered underwater glider is a torpedo-shaped autonomous underwater vehicle installing adjustable buoyancy bag and movable battery in it. The controller is composed of an LQR controller to maintain zigzag vertical movement for gliding and two PD controllers to control elevator/rudder angles. The LQR controller controls the pumping speed into the buoyancy bag and the moving speed to locate the battery. One of the PD controller controls the elevator angle to assist the LQR controller, and the other controls the rudder angle to adjust the direction of the underwater glider. A reduced order Luenberger observer is adopted to estimates the center of gravity of the glider and the buoyancy mass that are essential but cannot be measured. Mathematical simulation using Matlab proved the validity of the proposed controller to obtain better performance than conventional LQR only controller under the influence of sea current.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.705-709
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• 2005

In this paper, we introduce fuzzy algorithm similar to human's way of thinking and designed collision detection system of vehicles. First, before the model vehicles design, we did simulation collision detection using PID and Fuzzy Controller. As a result, P.O that is Percent Overshoot when make use of PID controller happened from smallest 32% to 45%. But, In case of using fuzzy controller they produced about 10% in 7% in case use 25 rule. We designed model vehicles that introduce Auto Guided Vehicle(AGV) with confirmed result in simulation. We set Polaroid 6500 sensor on the front of model automobile because distinguish existence automobile to the head. And we composed motor drive part to run vehicles and 80C196KC processor for control movement of vehicles influenced on distance data of the front vehicles that receive from supersonic waves sensor. In case of using Fuzzy controller, last value percent error happened about maximum 15% in smallest 5%, and we confirmed that distance with front vehicles kept when state hold time is about maximum 16 seconds in smallest 10 seconds.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.119-122
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• 2002

The paper proposed the intelligent inference method which keeps MV(Mobile vehicle) a little way off from men and makes it follow them using fuzzy controller Recognizing positions of MV and Men and distance between them was used to infer movement angle and speed of the MV with multi-ultrasonic sensor and USB camera The very important thing Is that the MV needs to obtain surrounding Information from the sensor and the camera, then It needs to represent those circumstances MV was controlled by inference from the speed and angle which are obtained from sensor and camera. Traveling simulation with a real MV was performed repeatedly to verify the usefulness of the fuzzy logic algorithm which was proposed in this paper. And a successful result of the experiment demonstrated the excellence of the fuzzy logic controller.

• Journal of Information Technology Services
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• v.22 no.3
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• pp.85-100
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• 2023

The development of Airside Vehicle Control System(AVCS) at Gimpo Airport aims to reduce ground safety accidents in movement area and improve airport operation efficiency and safety management service quality. The vehicle is controlled by a brake controller RTK-antenna and On-Board Diagonostics(OBD) module. Location data is transmitted to a nearby communication base station through a Wi-Fi router and the base station is connected to the AVCS by an optical cable to transmit location data from each vehicle. The vehicle position is precisely corrected to display information using the system. The system allows airport operators to view registered information on aircraft and vehicles and monitor their locations speeds and directions in real time. When a vehicle approaches a dangerous area alarm warnings and remote brake control are possible to prevent accidents caused by carelessness of the driver in advance.

• Journal of Mechanical Science and Technology
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• v.16 no.10
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• pp.1253-1263
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• 2002

The control system design and modeling of an unmanned vehicle by means of a new concept for better performance through a tole-operation system is suggested by sensor fusion. But, the control of a real vehicle is very difficult, because the system identification of the vehicle is hard to find the unknown factors and the disturbances of the experimental environment. For the longitudinal and lateral controls, the traction system and steering system models are set up and a tuning method to find the gain of the controller by experiments is presented. In this research, mechanical and electronic parts are implemented to operate the unmanned vehicle and data reconstruction method of information about the environment data coming from several sensors is presented by data plot for the vehicle navigation. This paper focuses on the integration of tole-operated unmanned vehicle. This vehicle mainly controlled lateral and longitudinal directions with actuators for controlling vehicle movement and sensors for the closed-loop controlled system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.4
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• pp.603-610
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• 1998

The purpose of this paper is to describe how the characteristics of the movement of cars can be modeled with computers. For this, we use Matlab and simulate the characteristics of the cruise-speed at which the car is driven using the Fuzzy PID controller. The model of the car is designed by M-S(Matlab-Simulink) and each parameter of PID is estimated automatically by the Fuzzy controller. The simulation of the car is carried out on straight base tracks, and then this is compared and analyzed with the simple Fuzzy controller and the simple PID controller.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.139-142
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• 2001

This paper presents a design of two gimbal system. One is two axes stabilized platform that is targeted to preserve direction while vehicle that is adhered antiaircraft fire, radar or EOTS is moving. The system maintains stabilization by recovering error using the rate gyro. The other is three axes gimbal system that is intended to simulate various angle movement in space and to test three axes gyroscope. This system determines gyro condition comparing gyro output value with converted motor encoder value.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.871-875
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• 1996

The Output feedback linear quadratic regulator control is applied to the design of active suspension system using 7 DOF full car model. The performance index reflects the vehicle vertical movement, pitch and roll motion, and minimization of suspension stroke displacements in the rattle space. The elements of gain matrix are approximately decoupled so that each suspension requires only local information to generate the control force. The simulation results indicates that the output feedback LQ controller is more effective than purely passive or full state feedback active LQ controllers in following the road profile at the low frequency range and suppressing the road disturbance at the high frequency ranges.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.391-402
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• 2015

In this paper, we present implementation of backward movement control of truck-trailer vehicles using a fuzzy mode-based control scheme considering practical constraints and computational overhead. We propose a fuzzy feedback controller where output is predicted with the delay of a unit sampling period. Analysis and design of the proposed controller is very easy, because it is synchronized with sampling time. Stability analysis is also possible when quantization exists in the implementation of fuzzy control architectures, and we show that if the trivial solution of the fuzzy control system without quantization is asymptotically stable, then the solutions of the fuzzy control system with quantization are uniformly ultimately bounded. Experimental results using a toy truck show that the proposed control system outperforms a conventional system.