• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2004.04a
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• pp.393-397
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• 2004

In these days, a scale of system is more and more complex and large. The centralized system has the operation management method to be limited in the large scale system. In this paper, we proposed ACOS(Autonomous decentralized Container terminal Operating System). It is applied to container terminal using by autonomous decentralized system which can solve the problem of the centralized operation system. Also, we can defined a function of the ACOS's sub-system and showed a flowchart on operation method for the ACOS.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.933-935
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• 1996

The simplifying method for the design of decentralized reduced order $H_{\infty}$ controller is considered in this paper. When the controller is reconstructed for the original system, the decentralized condition of the controller for the transformed system is generally destroyed with older simplifying method. In designing the decentralized controller, direct output feedthrough terms give some difficulties by using other station's input information. We proposed a new solution for this problem.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.92-98
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• 2005

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized teaming control based on adaptive control method. The original motivation of the teaming control field was loaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.209-213
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• 1987

This paper presents decentralized discrete-time system which is optimized by hierarchical control for process automation via the extended interaction balance method. This proposed method can control general matrix which input matrix is not block diagonalization. Also, this paper shows convergence condition of proposed method.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.40-47
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work the authors presented an iterative precision of linear decentralized learning control based on p-integrated teaming method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the loaming control field was learning in robots doing repetitive tasks such as on a]1 assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1464-1468
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• 1997

We propose a decentralized state estimation method in the multisensor state estimation problem. The proposed method bounds teh maximum energy gain from uknown external disturbances to the estimation errors in the suboptimal case. And we formulate aternative H/sip .inf./ filter gain equatiions with teh idea that the suboptimal H.$^{\infty}$ filter is the special form of Kalman filter filter whose state equations are defined in indefinite inner product spaces. Using alternative filter gain equations we design the decentralized $H^{\infty}$ state estimator which is composed of local filters and central fusion filter that are suboptimal in the $H^{\infty}$ sense. In addition, the proposed update equations between global and local data can reduce unnecessary calculation burden efficently.y.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.7
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• pp.370-377
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• 2000

This paper presents a decentralized compensator design procedure for large scale systems. By using a coordinate transformation method, interconnection terms in t도 subsystem are decoupled and a decentralized observer is designed independently as a form of Luenberger-type for each subsystem. And the decentralized compensator which can select the observer and controller gain independently is designed as a form of observer based controller for each subsystem. The proposed method has a simplicity and conciseness in the aspects of the determination of coordinate transformation matrices and the derivation of the separation principle which is adopted independently for each subsystem.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.528-533
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• 2004

The purpose of this thesis is to construct the autonomous decentralized train traffic management structure using techniques of Autonomous Decentralized System. Currently, a method of train traffic control is making use of CTC(Centralized Traffic Control). Its operation method is divided into the remote mode and the local mode. The classified basis is according to the control authority of install signals in track side. In most cases, a large scale station is operated by the local mode. Because of dispatchers in center can not control the shunting works influence on the main route. In order to solve these problem s, we analyzed a current operation condition and system requirements. Moreover, this thesis is constructing autonomous decentralized train traffic management structure. Finally, this research proposed that interface with CTC and step-by-step construction.