• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.207-212
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• 2003

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.181-186
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• 2004

This paper proposed trajectory tracking control of Mobile Robot. Trajectory tracking control scheme are Real coding Genetic-Algorithm and Back-propergation Algorithm. Control scheme ability experience proposed simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.188-190
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• 2000

This paper proposed design of robust fuzzy controller for nonlinear systems in the presence of parametric uncertainties. In the design procedure, we represent the nonlinear system using Takagi-Sugeno fuzzy model. A sufficient condition of the robust stability is presented in the sense of Lyapunov for the TSK fuzzy model with uncertainties. Finally, the effectiveness of proposed controller has been through a result of numerical simulation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.607-612
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• 1998

In this paper, a controller using fuzzy-genetic algorithms is proposed for pat-tracking of WMR. A fuzzy controller is implemented so as to adjust appropriate crossover rate and mutation rate. A genetic algorithms is also implemented to have adaptive adjustment of control gain during optimizing process. To check effectiveness of this algorithms, computer simulation is applied.

• Journal of the Korean Society of Industry Convergence
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• v.9 no.1
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• pp.79-86
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• 2006

In this study, we research and develope Intelligent Remote management controller. According to the load condition, we will apply various control techniques and plan high efficient Demand control. After development, According to the Demand Control, An electricity enterprisers will expect enlargement of equipment coefficient, elevation of back up load factor and reduction effect of equipment investment. On Customer side, They will expect reduction of electric fee, saving energy and variety of service choice.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2005.05a
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• pp.415-417
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• 2005

In this paper, we propose a intelligent controller design method for the water level control of the power plant drum in the form of nonminimum phase system. The proposed method is based on T. Takagi and M. Sugeno's fuzzy model. And we illustrate the improved characteristics as the simulation results, comparing with the conventional the PID and LQ controller design method

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.413-417
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• 2004

This paper proposes a fuzzy proportional-Integral (PI) controller for the precise tracking control of optical disk systems based on the genetic algorithm (GA). The fuzzy PI control rules are optimized by the GA to yield an optimal fuzzy PI controller. We validate the feasibility of the proposed method through a numerical simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.574-578
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• 2001

The stability analysis for the fuzzy logic controller (FLC) has widely been reported. Furthermore many research in the FLC has been introduced to decrease the number of parameters representing the antecedent part of the fuzzy control rule. In this paper we briefly explain a single-input fuzzy logic controller (SFLC) or simple-structured FLC which uses only a single input variable. And then we analyze that it is absolutely stale based on the sector bounded condition. We also show the feasibility of the proposed stability analysis through a numerical example of a mass-damper-spring system.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.384-388
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• 1999

This paper describes an approach for synthesizing a modularized gain scheduled PD type fuzzy logic controller(FLC) of nonlinear magnetic bearing system where the gains of FLC are on-line adapted according to the operating point. Specifically the systematic procedure via root locus technique is carried out for the selection of the gains of FLC. Simulation results demonstrate that the proposed gain scheduled fuzzy logic controller yields not only maximization of stability boundary but also better control performance than a single operating point (without gain scheduling)fuzzy controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.941-944
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• 1993

In this paper, we present an international benchmark used in the adaptive control specialist community in order to evaluated the fuzzy control performances. Before solving the corresponding problems, we introduce some improvements on a classic fuzzy controller in order to consider high order systems and time delays. At the end of this paper, the simulation results obtained with the extended Fuzzy Controller will be compared with those obtained with a Supervised Adaptive Controller.