• Journal of KSNVE
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• v.8 no.3
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• pp.494-503
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• 1998

In this paper, in order to analyze dynamic characteristics of an automobile steering system consisting of many components, natural frequencies and transfer functions of each component and the total system are found on a FFT analyzer by experiments. Then, the data are transmitted to a commercial package program, CADA-PC. By analyzing the data, the mode shape of each natural frequency and damping values are obtained. Also, the function of a rubber coupling in column and telescoping effects on system are considered. C.A.E commercial programs are used to compare with the results of experiments. For the finite element modeling, I-DEAS is used. Data processing and post processing are operated on NASTRAN and XL, respectively. The ball-bearing and the linkage of shaft with column are modeled by spring element. Stiffness is modified from the results of experiments. The results of those show close agreement. In the mode shape of total system, wheel mode is dominant at lower frequency, while the column mode is main mode at higher. The role of rubber coupling in vibration isolation is clear on mode shape. Telescoping function makes natural frequency of column changed.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.4
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• pp.353-360
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• 2010

A skid-steering method which applied to the various mobile robot platforms currently shows its effectiveness in the specified field areas and purposes. This system contains however, several problems of its intrinsic properties such as slippages occurred by different moving direction between vehicle's driving and wheel's rotary and difficulties of driving performance control and so on. This paper deals with the suggestion of suitable control algorithm for 6WD/6WS skid steering wheeled vehicle and verified its feasibility by analyzing the behavior of 6WD/6WS skid-steered wheeled vehicle model and by applying the engineering analytical method to the considered mobile platform. The Performance of vehicle model is evaluated by using slip mode control to follow the steering input and, as a future work, this control algorithm could be applied to real 6WD/6WS in-wheel drive type vehicle finally.

• Journal of Magnetics
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• v.20 no.1
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• pp.69-78
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• 2015

This paper focuses on the design of a flux-biased rotary electromagnetic actuator with compact structure for fast steering mirror (FSM). The actuator has high force density and its torque output shows linear dependence on both excitation current and rotation angle. Benefiting from a new electromagnetic topology, no additional axial force is generated and an armature with small moment of inertia is achieved. To improve modeling accuracy, the actuator is modeled with flux leakage taken into account. In order to achieve an FSM with good performance, a design methodology is presented. The methodology aims to achieve a balance between torque output, torque density and required coil magnetomotive force. By using the design methodology, the actuator which will be used to drive our FSM is achieved. The finite element simulation results validate the design results, along with the concept design, magnetic analysis and torque output model.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.196-196
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• 2000

This paper describes a lateral guidance system of an autonomous vehicle, using a neural network model of magneto-resistive sensor and magnetic fields. The model equation was compared with experimental sensing data. We found that the experimental result has a negligible difference from the modeling equation result. We verified that the modeling equation can be used in simulations. As the neural network controller acquires magnetic field values(B$\_$x/, B$\_$y/, B$\_$z/) from the three-axis, the controller outputs a steering angle. The controller uses the back-propagation algorithms of neural network. The learning pattern acquisition was obtained using computer simulation, which is more exact than human driving. The simulation program was developed in order to verify the acquisition of the teaming pattern, teaming itself, and the adequacy of the design controller. The performance of the controller can be verified through simulation. The real autonomous electric vehicle using neural network controller verified good results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.233-237
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• 2002

Vehicle Dynamics Control(VDC) has been a breakthrough and become a new terminology for the safety of a driver and improvement of vehicle handling. This paper examines the usefulness of a brake steer system (BSS), which uses differential brake forces for steering intervention in the context of VDC. In order to help the car to turn, a yaw moment can be achieved by altering the left/light and front/rear brake distribution. The steering function achieved through BSS can then be used to control lateral position in an unintended road departure system. A 8-DOF non-linear vehicle model including STI tire model will be validated using the equations of motion of the vehicle, and the non-linear vehicle dynamics. Since Fuzzy logic can consider the nonlinear effect of vehicle modeling, Fuzzy controller is designed to explore BSS feasibility, by modifying the brake distribution through the control of the yaw rate of the vehicle. The control strategies developed will be tested by simulation of a variety of situation; the possibility of VDC using BSS is verified in this paper.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2002.03a
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• pp.229-234
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• 2002

Immune system is an evolutionary biological system to protect Innumerable foreign materials such as virus, germ cell, and et cetera. Immune algorithm is the modeling of this system'response that has adaptation and reliableness when disturbance occur. In this paper, immune algorithm controller was proposed to control four wheels steering(4ws) Automated Guided vehicle(AGV) in container yard. And then the simulation result was analysed and compared with the results of NN-PID controller.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.932-937
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• 2003

In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.183-192
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• 2003

Obstacle detection and avoidance are considered as one of the key technologies on an unmanned vehicle system. In this paper, we propose a method of obstacle detection and avoidance and it is composed of vehicle control, modeling, and sensor experiments. Obstacle detection and avoidance consist of two parts: one is longitudinal control system for acceleration and deceleration and the other is lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control system of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. In this paper, we propose a method for vehicle control, modeling, and obstacle avoidance, which are evaluated through road tests.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2824-2826
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• 2002

Immune system is an evolutionary biological system to protect innumerable foreign materials such as virus, germ cell, and etcetera. Immune algorithm is the modeling of this systems response that has adaptation and reliability when disturbance occur. In this paper, immune algorithm is proposed to control four wheels steering AGV(Automated Guided Vehicle) in container yard. The adaptive immune system is applied to the PID controller. For design the PID controller using immune algorithm, we tune PID parameters by off-line manner, in order to avoid the damage from abrupt control force. Repeatedly, the PID parameters are adjusted to be accurate by on-line fine tuner of immune algorithm. And then the computer simulation result from the viewpoint of yaw rate and lateral displacement are analyzed and compared with result of conventional PID controller.

• International Journal of Automotive Technology
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• v.4 no.4
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• pp.173-180
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• 2003

Obstacle avoidance is considered as one of the key technologies in an unmanned vehicle system. In this paper, we propose a method of obstacle avoidance, which can be expressed as vehicle control, modeling, and sensor experiments. Obstacle avoidance consists of two parts: one longitudinal control system for acceleration; and deceleration and a lateral control system for steering control. Each system is used for unmanned vehicle control, which notes its location, recognizes obstacles surrounding it, and makes a decision how fast to proceed according to circumstances. During the operation, the control strategy of the vehicle can detect obstacles and perform obstacle avoidance on the road, which involves vehicle velocity. The method proposed for vehicle control, modeling, and obstacle avoidance has been confirmed through vehicle tests.