• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.33-36
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• 2002

In this paper, we propose a control method of an unknown nonlinear system using a dynamical neural network. The method proposed in this paper performs for a nonlinear system with unknown system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed algorithm, we simulated one-link manipulator. The simulation result showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.494-497
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• 2002

In this paper, we proposed a control method of an unknown nonlinear system using a dynamical neural network. The proposed method performs for a nonlinear system with unknown system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed method, we simulated one-link manipulator. The simulation results showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.141-150
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• 1998

This paper presents a dynamical anti-reset windup (ARW) compensation method for saturating control systems with multiple controllers and/or multiloop configuration. By regarding the difference of controller states in the absence and presence of saturating actuators as an objective function, the dynamical compensator which minimizes the objective function is derived in an integrated fashion. The proposed dynamical compensator is a closed form of plant and controller parameters. The resulting dynamics of compensated controller reflects the linear closed-loop system. The proposed method guarantees total stability of the resulting system. The effectiveness of the proposed method is illustrated by applying it to a servo motor control system. The paper is an extension of the results in Park and Choi[1].

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.397-406
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• 1997

In this paper we introduce GESS method and show that dynamics of the system ｙ＇=A(s,t,y) ｙ is more faithfully approxi-mated by GESS method that by Euler method. Numerical experiments are given for the comparison of GESS method with Euler method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.3
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• pp.487-492
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• 2002

In this paper, we proposed a control method of an unknown nonlinear system using a dynamical neural network. The proposed method is composed of neural network of state space model type, performs for a unknown nonlinear system, identification with using the dynamical neural network, and then a nonlinear adaptive controller is designed with these identified informations. In order to verify the effectiveness of the proposed method, we simulated one-link manipulator. The simulation results showed the effectiveness of using the dynamical neural network in the adaptive control of one-link manipulator.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.583-584
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• 2009

This paper provides a method to analyze the dynamical system. It considers the fact of realistic delay in dynamical system analysis for the first time. The method uses timeline and state space to emulate the inhibitive coupling nodes evolving procedure in transmission delayed environment. The resultant finite state machine shows the system predictability and hardware implementation feasibility.

• Bulletin of the Society of Naval Architects of Korea
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• v.2 no.1
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• pp.15-19
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• 1965

The stability curves are very important data to decide the seaworthiness of all kinds of ships among waves. Both statical and dynamical stability curves on a rectangular coordinate system have broadly been handled at ship yards or at the government concerned, up to data. As concerns a method of obtaining a statical stability curve on polar coordinate system, the papers were presented once. Also, it is of use to research the dynamical stability curve on polar coordinate system. Author treated of the dynamical stability curve by four different methods, and tried to set the stability indicator inboard, adopted those proposals, in order to give some aids for good navigation on the sea. Fig. 1. shows a drawing method in case of the position of centre of buoyancy can be previously pointed out on the line corresponding to its inclination. Fig. 2. shows a method used a statical stability curve on polar coordinate. Fig. 3. shows a method obtained by the most simplified means. Fig. 4. shows dynamical stability curve made by geometrical expression method, instead of dynamical lever. A simple stability indicator which was mechanized above characteristics is attempted by author as shown Fig. 5 and Fig.6. It is demanded at hand, for more advanced improvement of such indicator.

• Interaction and multiscale mechanics
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• v.3 no.1
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• pp.1-22
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• 2010

In this paper one introduces a method of multiscale modelling called collection of dynamical systems with dimensional reduction. The method is suggested to be an appropriate approach to theoretical modelling of phenomena in mechanics of materials having in mind especially dynamics of processes. Within this method one formalizes scale of averaging of processes during modelling. To this end a collection of dynamical systems is distinguished within an elementary dynamical system. One introduces a dimensional reduction procedure which is designed to be a method of transition between various scales. In order to consider continuum models as obtained by means of the dimensional reduction one introduces continuum with finite-dimensional fields. Owing to geometrical elements associated with the elementary dynamical system we can formalize scale of averaging within continuum mechanics approach. In general presented here approach is viewed as a continuation of the rational mechanics.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1165-1168
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• 1996

The neural network approach has been shown to be a general scheme for nonlinear dynamical system identification. Unfortunately the error surface of a Multilayer Neural Network(MNN) that widely used is often highly complex. This is a disadvantage and potential traps may exist in the identification procedure. The objective of this paper is to identify a nonlinear dynamical systems based on Radial Basis Function Networks(RBFN). The learning with RBFN is fast and precise. This paper discusses RBFN as identification procedure is based on a nonlinear dynamical systems. and A design method of model follow control system based on RBFN controller is developed. As a result of applying this method to inverted pendulum, the simulation has shown that RBFN can be used as identification and control of nonlinear dynamical systems effectively.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.73-76
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• 1996

This paper presents a dynamical anti-reset windup (ARW) compensation method for saturating control systems with multiple controllers and/or multiloop configuration. By regarding the difference of the controller states in the absence and presence of saturating actuators as an objective function, the dynamical compensator which minimize the objective function are derived in an integrated fashion. The proposed dynamical compensator is a closed form of the plant and controller parameters. The proposed method guarantees total stability of resulting system. An illustrative example is given to show the effectiveness of the proposed method.