• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.517-523
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• 2002

In this paper, we propose system that apply VIBL method to add speech recognition to LIBL method based on human s studying method to use natural language to steering system of ship, MERCS and winch appliances and use VIBL method to alternate process that linguistic instruction such as officer s steering instruction is achieved via ableman and control steering gear, MERCS and winch appliances. By specific method of study, ableman s suitable steering manufacturing model embodies intelligent steering gear controlling system that embody and language direction base studying method to present proper meaning element and evaluation rule to steering system of ship apply and respond more efficiently on voice instruction of commander using fuzzy inference rule. Also we embody system that recognize voice direction of commander and control MERCS and winch appliances. We embodied steering manufacturing model based on ableman s experience and presented rudder angle for intelligent steering system, compass bearing arrival time, evaluation rule to propose meaning element of stationary state and correct steerman manufacturing model rule using technique to recognize voice instruction of commander and change to text and fuzzy inference. Also we apply VIBL method to speech recognition ship control simulator and confirmed the effectiveness.

• Journal of Sensor Science and Technology
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• v.15 no.6
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• pp.425-432
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• 2006

This paper presents a control algorithm for smart actuators that can be used in a 'steer-by-wire' system for next-generation intelligent automobiles. 'Steer-by-wire' is a network-based mechatronic steering system in which mechanical linkages and hydraulics are replaced by electric motors and a digital communication network. The algorithm is designed not only to achieve the capabilities of following the desired steering angles while minimizing the discrepancy between two steering wheels, but also to tolerate an actuator with faults. The proposed algorithm is based on a simple proportional control so that it can be implemented in real-time with a low-cost embedded microcontroller. The effectiveness of the control algorithm is examined using a hardware-in-the-loop simulator consisting of two DC motors and a CAN bus network.

• Journal of the Institute of Convergence Signal Processing
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• v.4 no.4
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• pp.58-65
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• 2003

This paper studies a steering control method using a neural network algorithm for an intelligent autonomous driving robot. Previous horizontal steering control methods were made by various possible situation on the road. However, it isn't possible to make out algorithms that consider all sudden variances on the road. In this paper, an intelligent steering control algorithm for an autonomous driving robot system is presented. The algorithm is based on Self Organizing Maps(SOM) and the feature points on the road are used as training datum. In a simulation test, it is available to handle a steering control using SOM for an autonomous steering control. The algorithm is evaluated on an autonomous driving robot. The algorithm is available to control a steering for an autonomous driving robot with better performance at the experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.29-39
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• 1997

A discrete model reference control scheme for a vehicle four wheel steering system(4WS) is proposed and evaluated for a class of discrete time nonlinar dynamics. The schmen employs a neural network to identify the plan systems, wher the neural network estimates the nonlinear dynamics of the plant. The algorithm is proven to be globally stable, with tracking errors converging to the neighborhood of zero. The merits of this scheme is that the global system stability is guaranteed. Whith thd resulting identification model which contains the neural networks, the parameters of controller are adjusted. The proposed scheme is applied to the vehicle active four wheel system and shows the validity and effectiveness through simulation. The three-degree-of freedom vehicle handling model is used to investigate vehicle handing performances. In simulation of the J-turn maneuver, the yaw rate overshoot reduction of a typical mid-size car is improved by 30% compared to a two wheel steering system(2WS) case, resulting that the proposed scheme gives faster yaw rate response andl smaller side slip angle than the 2WS case.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.480-489
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• 1999

Design and experimental results of yaw rate controller is described for electricallydriven four wheel vehicle without steering mechanism. Yaw rate controller has been known to be necessary to cope with nonlinear char-acteristics of the wheel/road conditions with respect to different road condition and steering angle. For an effective yaw rate control, a fuzzy PID gain scheduler is considered with changing control parameters. In order to apply proposed algorithm to the system a downsized four wheel drive electrically driven vehicle without steering mechanism was manufactured. With these techniques the proposed yaw rate controller is shown by experiment results to be obtained suficient performance in the whole steering regions.

• Journal of Auto-vehicle Safety Association
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• v.5 no.2
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• pp.24-31
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• 2013

This paper describes a coordinated control algorithm for rear-side collision avoidance. In order to assist driver actively and increase driver's safety, the proposed coordinated control algorithm is designed to combine lateral control using a steering torque overlay by Motor Driven Power Steering (MDPS) and differential braking by Vehicle Stability Control (VSC). The main objective of a combined control strategy is twofold. The one is to prevent the collision between the subject vehicle and approaching vehicle in the adjacent lanes. The other is to limit actuator's control inputs and vehicle dynamics to safe values for the assurance of the driver's comfort. In order to achieve these goals, the Lyapunov theory and LMI optimization methods has been employed. The proposed coordinated control algorithm for rear-side collision avoidance has been evaluated via simulation using CarSim and MATLAB/Simulink.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1809-1815
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• 2003

This paper presents a human friendly system using fuzzy inference as a Part of study to embody intelligent ship. We also build intelligent ship's steering system to take advantage of speech recognition that is a part of the human friendly interface. It can bring an effect such as labor decrement in ship. In order to design the voice instruction based ship's steering gear control system, we build of the voice instruction based learning(VIBL) system based on speech recognition and intelligent learning method at first. Next, we design an quartermaster's operation model by fuzzy inference and construct PC based remote control system. Finally, we applied the unposed control system to the miniature ship and verified its effectiveness.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.104-104
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• 2000

Among durability tests, the accelerated durability test has been widely used to evaluate the durability of vehicle structure and chassis pans in a shon period of time on the designed road which has severe surface conditions. However it increases the drivers fatigue mainly caused by the severe driving conditions. The drivers difficulty of maintaining constant speed and controlling the steering wheel reduces the reliability of test results. The durability test includes the position and distance sensing system for the recognition of the absolute and relative driving position, the driving control system for the control of whole driving circumstance, the emergency system for responding to system errors. AGVDS (Autonomous Guided Vehicle Driving System) was Proved to facilitate the development of now car projects. Therefore the AGVDS we propose will help make the fundamentals for all future traffic systems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.305-309
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• 2006

The important field of research on ship operation is related to the high efficiency of transportation, the convenience of maneuvering ships and the safety of navigation. For these purposes, many intelligent technologies for ship automation have been required and studied. As a way of practical application for a smart ship based on network system, this paper proposes the intelligent control system for ship steering gear based on TCP/IP and desires to testify the validity of the proposal by applying the fuzzy control model to the steering gear system. As study method, the fuzzy inference was adopted to build the maneuvering models of steersman and then the network system was implemented using the TCP/IP Socket programming. Lastly, the miniature steering control system was designed to testify for its effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.747-756
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• 2002

The automatic steering system for unmanned vehicle was developed. The magnet and MR (Magnetoresistive) sensors are used for the tue detecting system. The lateral distance between sensor and the center line of the road is determined by the linearization of the distance according to the output. The PD control theory is used for the design of the controller to compare with $H_\infty$ control theory. The $H_\infty$ control theory is used for the design of the controller to reduce the disturbance. The performance of the PD controller and $H_\infty$ controller is compared in simulations and tests. The PD controller is easy to tune in the test site. The $H_\infty$ controller is robust far the disturbances in the test results.