• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.139-144
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• 1995

LIBL(Linguistic Instruction Based Leaning) is an effective learning algorithm for fuzzy controller which interpretes and uses natural language of human The possibiliy of the LIBL algorithm to the fuzzy control of dynamic systems is investigated in this paper. Rise time, percent overshoot, and steady stste are proposed as suitable meaning elements for dynamic systems. A supervisor is able to give "higer-level linguistic instruction" to the learning algorithm through these three meaning elements Simulation results for a DC servo motor show the validity of the proposed algorithm.

• Proceedings of KOSOMES biannual meeting
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• 2003.05a
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• pp.111-116
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• 2003

최근에는 전문가의 지식과 경험정보가 데이터베이스로 구축된 전문가 시스템의 정보를 이용하여 처리된 결과를 판단하여 안전하고 효율적인 선박운항이 가능하도록 한 지능형 선박에 관한 연구가 활발하게 진행되고 있다. 본 논문에서는 지능형 선박을 구현하기 위한 연구의 일환으로써, 선박의 조타기를 제어하기 위한 지능형 조타 조작 모델을 구현한다. 지능형 시스템을 구현하기 위해서 자연언어를 사용하는 인간의 학습 방법에 기초한 언어지시기반학습(LIBL)기법을 적용하고. 퍼지이론을 이용하여 승선경력이 풍부한 조타수의 경험을 조사 및 분석하여 그 결과를 바탕으로 퍼지 추론에 의해 타각을 제어하기 위한 퍼지 조타 조작 모델을 구현하여 그 효용성을 살펴보았다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.5
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• pp.417-423
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• 2002

In this paper, we propose intelligent steering control system that apply LIBL(Linguistic Instruction Based Learning) method to steering system of ship and take the place of process that linguistic instruction such as officer s steering instruction is achieved via ableman. We embody ableman s suitable steering manufacturing model using fuzzy inference rule by specific method of study, and apply LIBL method to present suitable meaning element and evaluation rule to steering system of ship, embody intelligent steering gear control system that respond more efficiently on officer s linguistic instruction. We presented evaluation rule to constructed steering manufacturing model based on ableman s experience, and propose rudder angle for steering system, compass bearing arrival time, meaning element of stationary state, and correct ableman manufacturing model rule using fuzzy inference. Also, we apply LIBL method to ship control simulator and confirmed the effectiveness.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.93-97
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• 2002

In this paper, we propose intelligent steering control system that apply LIBL(Linguistic Instruction Based Learning) method to steering system of ship and take the place of process that linguistic instruction such as officer's steering instruction is achieved via ableman. We embody ableman's suitable steering manufacturing model using fuzzy inference rule by specific method of study, and apply LIBL method to present suitable meaning element and evaluation rule to steering system of ship, embody intelligent steering gear control system that respond more efficiently on officer's linguistic instruction. We presented evaluation rule to constructed steering manufacturing model based on ableman's experience, and propose rudder angle for steering system, compass bearing arrival time, meaning element of stationary state, and correct ableman manufacturing model rule using fuzzy inference. Also, we apply LIBL method to ship control simulator and confirmed the effectiveness.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.301-306
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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. As a way of practical application for a smart ship based on network system, this paper proposes the intelligent support system for ship steering control system based on TCP/IP and desires to testify the validity of the proposal by applying the fuzzy control model to the steering control system. As the specific study methods, the fuzzy inference was adopted to build the maneuvering models of steersman, and then the network system was implemented using the TCP/IP socket-based programming. Lastly, the miniature model steering control system combined with LIBL (Linguistic Instruction-based Learning) was designed to testify for its effectiveness.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.539-546
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• 2007

The important field of research in 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. In this paper, we propose an intelligent voice instruction-based learning (VIBL) method and discuss the building of a ship's steering control system based on this method. The VIBL system concretely consists of two functions: a text conversion function where an instructor's inputted voice is recognized and converted to text, and a linguistic instruction based learning function where the text instruction is understood through a searching process of given meaning elements. As a study method, the fuzzy theory is adopted to build maneuvering models of steersmen and then the existing LIBL is improved and combined with the voice recognition technology to propose the VIBL. The ship steering control system combined with VIBL is tested in a ship maneuvering simulator and its validity is shown.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.329-333
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• 2003

최근 전문가의 지식과 경험정보가 데이터베이스로 구축된 전문가 시스템의 지식 정보를 이용하여 안전하고 효율적인 선박운항이 가능한 지능형 선박 시스템에 관한 연구가 활발하게 진행되고 있다. 인공지능기법을 이용하여 보다 인간 친화적인 시스템을 구현하고, 음성인식기술을 이용하여 원격으로 선박 조타기를 제어하여 조업자의 부담경감 및 인원절감의 효과를 가져올 수 있는 선박 조종시스템의 개발이 절실하다. 따라서, 본 논문에서는 PC를 기반으로 하여 일격으로 모형 선박의 조타기를 제어하는 시스템을 구축한다. 구체적인 연구방법으로는, 음성인식기술과 지능형 학습 기법을 바탕으로 음성지시기반학습 시스템을 구축하고, 퍼지 조타수 조작모델을 구현하여 PC 기반 원격 제어시스템을 구축한다. 또한, 구축된 원격 조타제어시스템을 축소된 선박모형(Miniature Ship) 시스템에 적용하여 그 효용성을 확인하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.287-291
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• 2003

현대의 선박운항에 있어서 선내 노동의 경감과 운항의 안정성 및 경제성 확보를 위하여 선박 자동화 및 원격 조종화가 이루어지고 있다. 또한, 선박조종 및 작업제어를 위하여 컴퓨터를 이용한 통합제어 시스템에 관한 연구도 활발하게 진행되고 있다. 그러나 소형선박 빛 어선과 같은 환경에서의 지능형 시스템에 관한 연구는 많이 부족한 실정이다. 인공지능기법을 이용하여 보다 인간 친화적인 시스템을 구현하고, 음성인식기술을 이용하여 원격으로 선박 조타기를 제어하여 조업자의 부담경감 및 인원절감의 효과를 가져올 수 있는 선박 조종시스템의 개발이 절실하다. 본 논문에서는 PC를 기반으로 하여 원격으로 모형 선박의 조타기를 제어하는 시스템을 구축하였다. 구체적인 연구 방법으로는, 음성인식기술과 지능형 학습 기법을 바탕으로 음성지시기반학습 시스템을 구축하고, 퍼지 조타수 조작모델을 구현하여 PC 기반 원격 제어시스템을 구현하였다. 또한, 구축된 원격 조타제어시스템을 축소된 선박모형(Miniature Ship) 시스템에 적용하여 그 효용성을 확인하였다.

• Journal of the Korean Institute of Navigation
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• v.23 no.2
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• pp.1-9
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• 1999

A trailer truck is a major equipment for transporting containers, and its driving is difficult due to two degrees of freedom which exist in the joint part between truck and trailer. Especially Backing a trailer truck to a parking home is a difficult exercise for all but the most skilled truck drivers. Normal driving instincts lead to erroneous movements. When watching a truck driver backing toward a parking home, one often observes the driver backing, going forward, backing again, going forward, etc., and finally backing to the desired position along the parking home. This paper discusses the design of the controller to control the steering of a trailer truck while only backing up to a parking home from an initial position. In this paper, we propose a backing up control system for a container trailer truck using fuzzy theory where the primitive fuzzy control rules are macroscopically designed using an expert's knowledge, and the control rules are regulated by LIBL(Linguistic Instruction Based Learning) to enable to back up successfully the trailer tuck to a parking home from arbitrary initial position. The validity of the proposed parking control system is shown by applying it to some initial positions on the simulator for container trailer truck.