• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.9
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• pp.18-25
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• 2012

Recently, the depletion of fossil fuel carbon dioxide emissions due to limitations in the internal combustion engine vehicles is rising concern about electric vehicle. Neighborhood Electric Vehicle(NEV) is maximum speed 60km/h and one day driving distances less than 80km. In this paper, Power Conversion Controller is proposed for Neighborhood Electric Vehicle. To verify the developed Power conversion Controller, Test performed integration test, max load, power density, efficiency. Confirmed that the vehicle can be applied.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.414-421
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• 2007

This paper presents a engine/brake integrated VDC(Vehicle Dynamic Control) system using neural network algorithm methods for wheel slip and yaw rate control. For stable performance of vehicle, not only is the lateral motion control(wheel slip control) important but the yaw motion control of the vehicle is crucial. The proposed NNPI(Neural Network Proportional-Integral) controller operates at throttle angle to improve the performance of wheel slip. Also, the suggested NNPID controller performs at brake system to improve steering performance. The proposed controller consists of multi-hidden layer neural network structure and PID control strategy for self-learning of gain scheduling. Computer Simulation have been performed to verify the proposed neural network based control scheme of 17 dof vehicle dynamic model which is implemented in MATLAB Simulink.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.151-158
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• 1996

As an approach to design the intelligent controller for an underwater vehicle, this paper will propose a neural controller with the fuzzy weight which can tune the ocntorl rule effectively. The initial weights of th efuzzy-neural controller are constructdd by priori-information based on fuzzy control theory and tuned automatically by learning. The proposed control scheme has two improtnat characteristics of adaptation and learning under the control environment. Also it has the advantage that the precise dynamic characteristics of an underwater vehicle may not be required. The effectiveness of the proposed scheme will be demonstrated by computer simulations of an underwater vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1161-1166
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• 1993

The performances of a vehicle active suspension system with an optimal variable structure controller are compared to those of passive suspension system and active suspension systems with sky-hook and optimal controllers. The quater car model has a 2 DOF which accounts for vertical motions of a sprung and a unsprung masses. The transient responses are analyzed when a vehicle passing through a bump with a constant speed and the frequency responses are analyzed for white noise input at wheel. Particulary, RMS responses are also analyzed. It is shown that the optimal variable structure controller gives better performance of the vehicle active suspensio system than an optimal and a sky-hook controller.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.584-589
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• 2000

When the liquid tanks only partially filled and under translational acceleration, large quantities of liquid move uncontrollably inside the tanks and generate the liquid sloshing effect. Liquid sloshing effect could be a severe problem in launch vehicle stability and control if the liquid modes of motion couple significantly with the launch vehicle's normal modes of motion. Several methods have been employed to reduce the effect of sloshing, such as introducing baffles inside the tanks or dividing a large tank into a number of smaller ones. These techniques, although helpful in some cases, do not succeed in canceling the sloshing effects. In this paper, An attitude controller is designed for a launch vehicle with liquid sloshing effect. Both PD controller and sloshing filter are designed for the objective. PD gains and design parameters are determined by optimal algorithm. The performance of the attitude controller is evaluated via computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.8
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• pp.367-375
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• 2001

In Underwater Flight Vehicle depth control system, the followings must be required. First, it needs robust performance which can get over modeling error, parameter variation and disturbance. Second, it needs accurate performance which have small overshoot phenomenon and steady state error to avoid colliding with ground surface or obstacles. Third, it needs continuous control input to reduce the acoustic noise and propulsion energy consumption. Finally, it needs interpolation method which can sole the speed dependency problem of controller parameters. To solve these problems, we propose a depth control method using Fuzzy Sliding Mode Controller with feedforward control-plane bias term and Neural Network Interpolator. Simulation results show the proposed method has robust and accurate control performance by the continuous control input and has no speed dependency problem.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.2
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• pp.61-68
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• 2005

This paper is concerned with attitude control of 2 rotor 1 DOF aerial vehicle. The proposed controller consists of two parts: the attitude estimation filter part and PID controller part. For attitude estimation, performance of 3 different filters (complementary filters, Kalman filter, indirect Kalman filters) are tested and compared. For the PID controller, characteristic ratio assignment methods are used to assign PID coefficients. Through experiments, it is shown that attitude of the vehicle successfully follows the step command.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.274-281
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• 1998

This paper describes a visual control of autonomous vehicle using neural network. Visual control for road-following of autonomous vehicle is based on road image from camera. Road points on image are inputs of controller and vehicle speed and steering angle are outputs of controller using neural network. Simulation study confirmed the visual control of road-following using neural network. For experimental test, autonomous electric vehicle is designed and driving test is realized

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.6
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• pp.59-67
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• 2014

A numerical model and a controller of Active Front wheel Steer (AFS) system are designed in this study. The AFS model consists of four sub models, and the AFS controller uses sliding mode control and PID control methods. To test this model and controller an Integrated Dynamics Control with Steering (IDCS) system is also designed. The IDCS system integrates an AFS system and an ARS (Active Rear wheel Steering) system. The AFS controller and IDCS controller are compared under several driving and road conditions. An 8 degree of freedom vehicle model is also employed to test the controllers. The results show that the model of AFS system shows good kinematic steering assistance function. Steering ratio varies depends on vehicle velocity between 12 and 24. Kinematic stabilization function also shows good performance because yaw rate of AFS vehicle tracks the reference yaw rate. IDCS shows improved responses compared to AFS because body side slip angle is also reduced. This result also proves that AFS system shows satisfactory result when it is integrated with another chassis system. On a split-m road, two controllers forced the vehicle to proceed straight ahead.

• Journal of IKEEE
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• v.24 no.4
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• pp.1184-1187
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• 2020

This paper proposes an in-vehicle network controller fully exploiting the advantages of UART (Universal Asynchronous Receiver/Transmitter) and CAN (Controller Area Network). UART is used in 1-to-1 communication and it exploits parity bit for data integrity check. The proposed in-vehicle network controller converts UART into CAN, which enables multiple communications along with 1-to-1 communication. Also, the proposed in-vehicle network controller exploits CRC (cyclic redundancy check) for data integrity check, which increases communication reliability. CAN is controlled by microprocessor, but the proposed in-vehicle network controller can be controlled by any devices compliant with RS-232, RS-422, and RS-485.