• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.203-206
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• 2002

This paper describes fuzzy control methodologies of the steam generator which have nonlinear characteristics in the nuclear power plant. Actually, the steam generator part of the power generator has a problem to control water level because it has complex components and nonlinear characteristics. In order to control nonlinear terms of the model, Takagj-Sugeno (75) fuzzy system is used to design a controller. In designing procedure, intelligent digital redesign method is used to control the nonlinear system. This digital controller keeps the performance of the analog controller. Simulation examples are included for ensuring the proposed control method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.675-679
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• 2005

This paper deals with the problem of gust load alleviation in active control for the case that aeroelasticity takes place due to interaction between wing structure and aerodynamics on wing when aircraft meets gust during flight. Aeroservoelasticity model includes wing structure modeled in FEM, unsteady aerodynamics in minimum state approximate method, and models of actuator and sensors in state space. Based on this augmented model, digitally redesigned gust load alleviation system is designed in sampled-data control technique. From numerical simulation, this digital control system is effective to gust load on aircraft wing, which is shown in transient responses and PSD analysis to random gust inputs.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.28 no.1
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• pp.27-38
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• 1992

The paper presents a digital speed control approach of induction motor systems by using a digital redesign method and adopting a well known 2nd order model as the system model equation. The basic concept using the modeling equation is induced from the control theory stand point such that we can describe usually the motor system connected by inverter, generator and load etc. just as a mechanical system to be controlled. The concept does not demand us the complicated vector-based modeling equation adopted in the traditional methods for the speed control of induction motor. The effectiveness of the servo control system composed by the above mentioned design concept is illustrated by the experimental results in the presence of step reference change and generator load variation. It is observed from the experimental results that the steady state error of the experimental set up becomes zero after some regulation time and the induction motor system is robust in spite of reference signal change and load variation of generator.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.520-525
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• 2003

This paper concerns a design methodology of observer-based output-feedback digital controller for Takagi-Sugeno(TS) fuzzy systems using intelligent digital redesign (IDR). The term of IDR involves converting an analog fuzzy-mode-based controller into an equivalent digital one in the sense of state-matching. The considered IDR problem is viewed as convex minimization problems of the norm distances between linear operators to be matched. The stability condition is easily embedded and the separations principle is explicitly shown.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.318-323
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• 2005

In this paper, we propose a systematic method of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear system. A parallel distributed compensation (PDC) technique is then used to design a fuzzy model based controller for both stabilization and tracking. Finally, the designed continuous-time controller is converted to an equivalent discrete-time controller by using an intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy model based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, the single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Journal of Digital Convergence
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• v.12 no.5
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• pp.125-130
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• 2014

The competitiveness in today's global market forces many companies to develop families of products to provide enough variety for the marketplace. The challenge when designing a product family is in resolving the tradeoff between product commonality and distinctiveness. Simultaneously it is necessary to consider environmental performance to design a product family as well as to shorten lead-times, improve quality and reduce costs. This paper proposes a metaheuristic algorithm based redesign methodology for green product family considering environmental performance. The proposed method uses a genetic algorithm as metaheuristic algorithm and green product family index (GPFI) to support green product family design. In addition, it provides the redesign methodology such as product family level and component level. A case study used table lamps as an product family's example shows the verification and effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2480-2482
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• 2005

This paper presents a complete solution to intelligent digital redesign problem (IDR) for sampled-data fuzzy systems. The IDR problem is the problem of designing a sampled-data state feedback controller such that the sampled-data fuzzy system is equivalent to the continuous-time fuzzy system in the sense of the state matching. Its solution is simply obtained by linear transformation. Under the proposed sampled-data controller, the states of the discrete-time model of the sampled-data fuzzy system completely matches the state of the discrete-time model of the closed-loop continuous-time fuzzy systems are completely matched at every sampling points.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.142-145
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• 2000

A new robust load-frequency control (LFC) methodology is proposed for nonlinear power systems with the valve position limits of the governor in the presence of parametric uncertainties. The Takagi-Sugeno (TS) fuzzy model is adopted for fuzzy modeling of the nonlinear power system. A sufficient condition of the robust stability is presented in the sense of Lyapunov for the TS fuzzy model with parametric uncertainties. The intelligent digital redesign technique for the uncertain nonlinear power system is also studied. The effectiveness of the proposed robust fuzzy LFC controller design method is demonstrated through a numerical simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.7
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• pp.881-886
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• 2005

This paper presents intelligent digital redesign method of global approach for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent tile complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the power series, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of tile digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.700-705
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• 2012

This paper addresses an intelligent digital redesign (IDR) technique for observer-based output-feedback control systems, in order to efficiently convert a pre-designed Takagi-Sugeno fuzzy model-based analog controller into a sampled-data one in the sense of state matching. A delta operator is used to get an asymptotic relation between the analog and the sampled-data control systems. The IDR problem is viewed as a minimization problem of the norm distances between linear operator to be matched. The condition is represented as linear matrix inequalities, and the separation principle on the IDR is shown.