• Journal of Mechanical Science and Technology
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• 제20권1호
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• pp.29-41
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• 2006

Nowadays, with the advancement of computers, computer simulation linked with VR (Virtual Reality) technology has become a useful method for designing the automotive driving system. In this paper, the VR simulation system was developed to investigate the driving performances of the ASV (Advanced Safety Vehicle) equipped with an ACC (Adaptive Cruise Control) system. For this purpose, VR environment which generates visual and sound information of the vehicle, road, facilities, and terrain was organized for the realistic driving situation. Mathematical models of vehicle dynamic analysis, which includes the ACC algorithm, have been constructed for computer simulation. The ACC algorithm modulates the throttle and the brake functions of vehicles to regulate their speeds so that the vehicles can keep proper spacing. Also, the real-time simulation algorithm synchronizes vehicle dynamics simulation with VR rendering. With the developed VR simulation system, several scenarios are applied to evaluate the adaptive cruise controlled vehicle for various driving situations.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1014-1019
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• 2005

In this paper, a neural network technique for automatic steering control of a four wheel drive autonomous highway snowplow vehicle is presented. Controllers are designed by the LQR method based on the vehicle model. Then, neural network is used as an auxiliary controller to minimize lateral tracking error under the presence of load. Simulation studies of LQR control and neural network control are conducted for the vehicle model under a virtual snowplowing situation. Tracking performances are also compared for two and four wheeled steering vehicles.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.237-244
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• 2022

Eco-driving of vehicles today presents an advantage that aims to reduce energy consumption and limit CO2 emissions. The application for this option is possible to older vehicles. In this paper, we propose an efficient implementation for IoT (Internet of Things) system for controlling vehicle components that affect the quality of driving (acceleration, braking, clutch, gear change) via Smartphone using Wi-Fi and BLE as communication protocol. The user can see in real-time data from sensors that control driver action on vehicle driving systems such as acceleration, braking, and vehicle shifting through a web interface. Thanks to this communication, the user can control his driving quality and, hence, eco-driving can be achieved

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.496-500
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• 1998

Not merely running at the designated constant speed as the classical cruise control, the adaptive cruise control (ACC) maintains safe headway distance when the front is blocked by other vehicles. One of the most essential part of ACC System is the range sensor which can measure the position and speed of all objects in front continuously, ignore all irrelevant objects, distinguish vehicles in different lanes and lock on to the closest vehicle in the same lane. In this paper, the hierarchical object recognition algorithm (HORA) is proposed to process raw scanning laser data and acquire valid distance to target vehicle. HORA contains two principal concepts. First, the concept of life quantifies the reliability of range data to filter off the spurious detection and preserve the missing target position. Second, the concept of conformation checks the mobility of each obstacle and tracks the position shift. To estimate and predict the vehicle position Kalman filter is used. Repeatedly updated covariance matrix determines the bound of valid data. The algorithm is emulated on computer and tested on-line with our ACC vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.338-341
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• 1996

A neural fuzzy control strategy, developed in order to make a Mobile Vehicle(MV) run along with the traffic guidelines on the road, is presented. A neurocomputer is used in the control procedure and it learnt the driving knowledge to control the MV's actions. The image information of the guidelines is provided by a CCD camera on the top of the MV. The MV utilize the image information to identify the shape of the road and to decide the position of itself, and control the running actions. A fuzzy controller works on-line. Both of the neural controller and the fuzzy controller make up each other. This control method solve the problem of mechanical and electrical inertia and make the Mobile Vehicle run rapidly and smoothly.

• 제어로봇시스템학회논문지
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• 제6권10호
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• pp.936-941
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• 2000

Advanced space transportation systems, such as the National Aerospace Plane or an Orbital Transfer Vehicle, have atmospheric maneuvering capabilities. For such vehicles the use of aeroassisted orbital transfer from a high Earth orbit to a low Earth orbit, with unpowered flight in the atmosphere, has the potential for significant fuel savings compared to exoatmospheric Hohmann transfer. However, to exploit the fuel savings that can be achieved by using the Earths atmosphere to reduce the vehicles energy, a guidance law is required, and it must be able to handle large unpredictable fluctuations in atmospheric density, on the order of ${\pm}$50% relative to the 1962 US Standard Atmosphere. In this paper aeroassisted orbital transfer is considered as a differential game, with Nature controlling the atmosphere density to yield a worst case (min-max fuel required) atmosphere, from which the guaranteed playable set boundary are achieved. Inside the playable set, it is guaranteed that the vehicle achieves the optimal atmospheric exit condition for the minimum fuel consumption regardless of the atmospheric density variations.

• 제어로봇시스템학회논문지
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• 제8권7호
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• pp.613-623
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• 2002

Ascent trajectory optimization and explicit guidance problems for a satellite launch vehicle with yaw maneuver in a 3-dimension are considered. The trajectory optimization problem with boundary conditions is formulated as a nonlinear programming problem by parameterizing the inertial pitch and yaw attitude control variables, and is solved by using the SQP algorithm. The flight constraints such as gravity-turn and range safety conditions are imposed. An explicit inertial guidance algorithm in the exoatmospheric phase is also presented. The guidance algorithm provides steering command and time-to-go value directly using the current states of the vehicle and the desired orbit insertion conditions. The liquid propelled Delta 2910 launch vehicle is used as a numerical model.

• 전기학회논문지
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• 제62권8호
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• pp.1157-1162
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• 2013

This thesis describes the active cruise control which is a part of AVHS(Advanced Vehicle and Highway System) in the ITS(Intelligent Transportation Systems). The active cruise control is a system which recognizes some obstructions and vehicles in front, drives in safe speed and puts on the brake in dangerous situations as the driver simply turns on the switch without stepping on the accelerator and brake. PID controller is used in the speed-control by linearizing the longitudinal model of the vehicle, obstacle detecting algorithm which makes use of the laser scanner is proposed to recognize the situation in front and the system's performance is tested.

• 한국산학기술학회논문지
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• 제21권6호
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• pp.170-177
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• 2020

본 논문은 전기기계식제동장치(EMB : Electro Mechanical Brake, 이하 EMB)의 제동 압부력(clamping force) 제어방법과 제동시험장비(dynamo test equipment)를 활용한 제동성능 평가결과에 대하여 다룬다. EMB와 관련한 연구는 자동차 분야에서 대부분 수행되었으며, 다양한 제어방법에 대한 정적상태의 압부력 시험결과를 주로 다루고 있으나 본 논문은 동적상태에서의 성능평가를 수행하였다. EMB의 구동을 위해 3상 매입형 영구자석 동기전동기(IPMSM : Interior Permanent Magnet Synchronous Motor, 이하 IPMSM)가 적용되었으며 유한요소법(FEM : Finite Element Method, 이하 FEM) 해석 소프트웨어인 JMAG을 통하여 설계 및 해석을 수행하였다. EMB의 압부력제어를 위해 전류제어, 속도제어 및 위치제어가 수행되었으며, 전류제어기는 단위전류당 최대토크제어(MTPA : Maximum Torque Per Ampere, 이하 MTPA)가 적용되었다. 제동성능평가는 공압식 제동장치의 비상제동 성능시험 절차와 동일한 방법으로 수행되었으며 시험장비에 설치된 고속철도차량의 차륜을 110 km/h, 230 km/h 및 300 km/h로 회전하는 상태에서 각각의 속도 조건에 따른 EMB의 제동 압부력을 인가하여 감속성능을 확인하였다. 최고속도(300 km/h) 상태에서 비상제동 시험결과는 73초의 시간이 소요되었으며 차세대고속철도차량(HEMU-430X)에 적용된 공압식 제동장치의 성능시험 결과와 비교를 통하여 제동소요 시간 및 감속패턴의 유사함 확인하였다.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.702-708
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• 2013

Underwater TRN (Underwater Terrain Referenced Navigation) estimates an underwater vehicle state by measuring a distance between the vehicle and undersea terrain, and comparing it with the known terrain database. TRN belongs to absolute navigation methods, which are used to compensate a drift error of dead reckoning measurements such as IMU (Inertial Measurement Unit) or DVL (Doppler Velocity Log). However, underwater TRN is different to other absolute methods such as USBL (Ultra-Short Baseline) and LBL (Long Baseline), because TRN is independent of the external environment. As a magnetic-field-based navigation, TRN is a kind of geophysical navigation. This paper develops an EKF (Extended Kalman Filter) formulation for underwater TRN. A filter propagation part is composed by an inertial navigation system, and a filter update is executed with echo-sounder measurement. For large-initial-error cases, an adaptive EKF approach is also presented, to keep the filter be stable. At the end, simulation studies are given to verify the performance of the proposed TRN filter. With simplified sensor and terrain database models, the simulation results show that the underwater TRN could support conventional underwater navigation methods.