• Journal of Institute of Control, Robotics and Systems
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• v.21 no.3
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• pp.210-216
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• 2015

This paper proposes a method to determine vehicle driving state using the driving characteristics index. This index is a quantitative value to classify the driving state of a vehicle with its velocity and heading angle in that instant. It can classify driving state into straight driving, lane changing driving and curve driving in real time. In addition, the number of positional information is movably set up by designed region of interest. The proposed index is expressed on the stable driving states. Each driving state has characteristic tendency, and is compared with index distributional areas. The proposed method is verified by the actual driving experiment on the KATECH proving ground.

• 한국정보디스플레이학회:학술대회논문집
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• 2003.07a
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• pp.702-705
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• 2003

We reported the result of driving PDP's in selective erase scheme and three wall charge states. Compared to the selective write driving scheme, the selective erase scheme achieved flicker free half-ON state with much simpler driving waveforms than the selective write scheme. We believed that this improvement was possible since the cells entering the address period with enough wall charges to modulate easily with.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.211-214
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• 2002

We present gray scale implementation method based on QMA driving technique. We clarified the mechanism of wall charge quantization through discharge current measurement. We used three wall charge states to implement gray scale. The cells would be one of fully-ON, half-On, and OFF states. We built a five sub-fields 243 level gray scale with sustain pulse count of 2, 6, 18, 54, and 162.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.583-586
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• 2003

There are electric four-wheeled vehicles to assist elder people. Because of the vehicles'dynamic characteristic such as impossible to move abeam, it is difficult for these people who has little experience and has little knowledge to drive. Also to judge the future state of dynamic obstacles and to decide how to elude them safely are more difficult. We installed the predictive fuzzy controller(evaluates the future states which several kinds of operation candidates were done and chooses the best one) that modeled humans'algorithms in the system. Human predicts the future states of dynamic obstacles and chooses an operation(wait, steer, go back, etc) to elude safely. To elude dynamic obstacles flexibly, we added expert's knowledge for safe driving to this controller. In this paper, we propose the intelligent soft driving system by the controller that can elude dynamic obstacles safely, and we confirm the effectiveness by a simulation.

• 전기의세계
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• v.21 no.3
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• pp.31-40
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• 1972

This study intends to investigate the optimal switching modes of a double-capacitive thermal system under different constraints on the state and the control variable, by the application of the Pontryagin's Minimum Principle. Throughout the development, the control effort is assumed to have two modes of state: M or zero and the terminal times being fixed. In the first part of this study, the Principle is discussed under various conditions for this particular problem, with different criterion functions and in the same time imposing a certain constraints; i) on the terminal states, ii) on functions of the terminal states. Depending upon the upper bound value of the control vector, possible driving modes of the states are studied from which particular optimal driving modes are extracted so as to meet the specified constraints and boundary conditions imposed in the problem. Numerical solutions are evaluated for an over0damped, double-capacitive thermal plant and the optimal solutions: the switching mode, the optimal switching time, and the control effort are compared with the analytical results, in the second part of this work, to confirm the development.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.12
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• pp.122-129
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• 1995

The most important feature of a-Si TFT is dense localized states such as dangling bonds which exist in tis bandgap. Electrons trapped by localized states dominate the potential distribution in the active a-Si region ,and influence the performance of a-Si TFT. In this paper, we describe the electrical characteristics of a-Si TFT with respect to trap distribution within bandgap, electron mobility and interface states using 2-Dimensional device simulator and compare the result of simulation with measurements. Using the mixed-mode simulator, we can predict the potential variation of pixel which causes residual image problem during the turn-off of a-Si TFT driving circuit. Therefore it is possible to consider trade-off between potential variation of pixel and turn-on current of a-Si TFT for the optimized driving circuit.

• Journal of Industrial Technology
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• v.27 no.A
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• pp.141-147
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• 2007

In this paper, we define the multi-states exponential cell resident time mobility model for describing the mobility characteristics of mobile user and analyzed the total cost of the hybrid method using multi-states cell resident time. Generally, the mobile user has three states for its movement, such as staying, walking and driving. This multi-states cell resident time based hybrid method reflects the movement characteristics of mobile user and adapts the location update period according to the states of mobility speed. As a results of the performance analysis, we can get the optimum parameters of the hybrid method for multi-states based mobile users.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.5
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• pp.575-582
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• 2019

Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.1
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• pp.150-157
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• 2016

In this paper, a control system for E-bike based on IOT was developed, which collects and monitors information of states of E-bike and surrounding environments from several sensors and control devices in E-bike, and informs the possible dangers to rider when riding the E-bike. Developed electronic control system can manage battery efficiently, obtain battery's remaining power in real-time and provide possible riding distance to rider. It makes possible for rider to schedule near optimal riding route in terms of battery usage and respond quickly to battery discharge. Results of applying developed system to E-bike show that according to driving-mode, possible driving distance can be calculated efficiently and using user application App, real-time driver position marking and driving route searching functions lead to energy efficient E-bike driving. Later we will endeavor to integrate BMS, ECU, smart-phone and PC(server) to provide stable driving system based on various driving information of E-bike.