• Korean Journal of Agricultural Science
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• v.37 no.1
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• pp.123-130
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• 2010

A steering control system based on CAN(Controller Area Network) for autonomous tractor was developed to reduce duty of a central processing computer and to improve performance of steering control in terms of reduced control interval and error. The steering control system consisted of a SCU (Steering Control Unit), an EHPS system, and a potentiometer. The SCU consisted of an MCU (Micro Controller unit), an A/D converter, and a DC-DC converter, and a PID controller was used to control steering angle. The steering control system was communicated with the computer by CAN-bus. Each actuator and implement was connected to a multi-function board interfacing with the computer through a USB cable. Without CAN, control interval of the autonomous tractor was 1.5 seconds. When the CAN-based steering control system was combined with the autonomous tractor, however, control interval of the integrated system was reduced to those less than 0.05 seconds. When the autonomous tractor was operated with 1.5-s and 0.05-s control cycles at a 0.63-m/s travelling speed, the trajectories were close to straight lines for both of the control cycles. For a 1.34-m/s traveling speed, tractor trajectory was close to sine wave with a 1.5-s control cycle, but was straight line with a 0.05-s control cycle.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.687-690
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• 2000

Lately, many studies have been progressed for the protection human's lives and property as holding in check accidents happened by human's carelessness or mistakes. One part of these is the development of an autonomouse vehicle. General control method of vision-based autonomous vehicle system is to determine the navigation direction by analyzing lane images from a camera, and to navigate using proper control algorithm. In this paper, characteristic points are abstracted from lane images using lane recognition algorithm with sobel operator. And then the vehicle is controlled using two proposed auto-steering algorithms. Two steering control algorithms are introduced in this paper. First method is to use the geometric relation of a camera. After transforming from an image coordinate to a vehicle coordinate, a steering angle is calculated using Ackermann angle. Second one is using a neural network algorithm. It doesn't need to use the geometric relation of a camera and is easy to apply a steering algorithm. In addition, It is a nearest algorithm for the driving style of human driver. Proposed controller is a multilayer neural network using Levenberg-Marquardt backpropagation learning algorithm which was estimated much better than other methods, i.e. Conjugate Gradient or Gradient Decent ones.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.5
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• pp.349-359
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• 2022

The aim of this study is to analyze the dynamic characteristics of proportional control valves according to various working conditions as a basic study for developing proportional control valves for auto-steering tractors. The dynamic characteristics of proportional valves were measured using hydraulic characteristics measurement system, and the power was analyzed using measured flow rate and pressure data. As the experimental conditions, the tractor engine speed and steering angle was selected as the main variables, and the experiment was performed on urethane road conditions. As a result, it was found that the flow rate, pressure, and power of the proportional control valve increased as the tractor engine speed and steering angle increased. In particular, as the steering angle increased at the same engine speed, the flow rate, pressure, and power tended to increase by up to 190%, 172%, and 273%, respectively. Similarly, as the engine speed increased at the same steering angle, the flow rate, pressure, and power tended to increase up to 161%, 122%, and 168%, respectively. Therefore, it can be seen that the steering angle has a higher influence on the dynamic characteristics of the proportional control valve than the engine speed.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.209-211
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• 2006

Auto Steering System is the device for course keeping or course altering to ship's steering system. The purpose of automatic steering system is to keep the ship's course stable with the minimum course and rudder angle. Recently, modern control theories are being used widely in analyzing and designing the ship system. Though P.D type auto pilots are widely used in ships, the stability and the adjusting methods are not clarified. In this paper the authors proposed auto steering system with Hybrid Controller. The things that the actual operators of a steering wheel has acquired through their experience can be logically described by the Lingustic Control Rule. The characteristic of the control system were investigated through the computer simulation results. it was found that the Hybrid control was more efficient than the PD control system.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.114-117
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• 2005

Auto Steering System is the device for course keeping or course altering to ship's steering system. The Purpose of automatic steering system is to keep the ship's course stable with the minimum course and rudder angle. Recently, modern control theories are being used widely in analyzing and designing the ship system. Though P.D type auto pilots are widely used in ships, the stability and the adjusting methods are not clarified. In this paper the authors proposed auto steering system with Fuzzy Logic Controller. In the fuzzy control the things that the actual operators of a steering wheel has acquired through their experience can be logically described by the Lingustic Control Rule. The characteristic of the control system were investigated through the computer simulation results. it was found that the fuzzy logic control was more efficient than the conventional system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.383-387
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• 1996

This paper presents a steering control strategy applicable to vehicle path following problems. This control strategy is based on realistic nonlinear equations of motion of multibody systems described in terms of relative joint coordinates. The acceleration of the steering angle is selected as a control input of the system. This input is obtained by considering position and slope errors at current and at advance times. This steering control strategy is tested in circular and lane change maneuvers with a nonlinear vehicle model.

• Proceedings of the KSME Conference
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• 2007.05a
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• pp.855-860
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• 2007

This paper describes a human driver model developed based on finite preview optimal control method. The human driver steering model is constructed to minimize a performance index which is a quadratic form of lateral position error, yaw angle error and steering input. Simulation studies are conducted using a vehicle simulation software, Carsim. The Carsim vehicle model is validated using vehicle test data. In order to validate the human driving steering model, the human driver steering model is compared to the driving data on a virtual test track(VTT) and the actual vehicle test data. It is shown that human driver steering behaviors can be well represented by the human driver steering model presented in this paper

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.513-520
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• 2011

This paper presents the motion planning of robotic vehicles for the path tracking and the obstacle avoidance. To follow the given path, the vehicle moves through the turning radius obtained through the pure pursuit method, which is a geometric path tracking method. In this paper, we assume that the vehicle is equipped with a 2D laser scanner, allowing it to avoid obstacles within its sensing range. The turning radius for avoiding the obstacle, which is inversely proportional to the virtual force, is then calculated. Therefore, these two kinds of the turning radius are used to generate the steering angle for the front wheel of the vehicle. And the vehicle reduces the velocity when it meets the obstacle or the large steering angle using the potentials of obstacle points and the steering angle. Thus the motion planning of the vehicle is done by planning the steering angle for the front wheels and the velocity. Finally, the performance of the proposed method is tested through simulation.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.17-23
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• 2012

An integrated dynamic control (IDCF) with an active front steering system and an active rear braking system is proposed and developed in this study. A fuzzy logic controller is applied to calculate the desired additional steering angle and desired slip of the rear inner wheel. To validate IDCF system, an eight degree of freedom, nonlinear vehicle model and a sliding mode wheel slip controller are also designed. Various road conditions are used to test the performance. The results show that the yaw rate of IDCF vehicle followed the reference yaw rate and reduced the body slip angle, compared with uncontrolled vehicle. Thus, the IDCF vehicle had enhanced lateral stability and controllability.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.65-70
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• 2014

An Integrated Dynamics Control system with four wheel Steering (IDCS) is proposed and analysed in this study. It integrates and controls steer angle of front and rear wheel simultaneously to enhance lateral stability and steerability. An active front steer (AFS) system and an active rear steer (ARS) system are also developed to compare their performances. The systems are evaluated during brake maneuver and several road conditions are used to test the performances. The results showed that IDCS vehicle follows the reference yaw rate and reduces side slip angle very well. AFS and ARS vehicles track the reference yaw rate but they can not reduce side slip angle. On split-${\mu}$ road, IDCS controller forces the vehicle to go straight ahead but AFS and ARS vehicles show lateral deviation from centerline.