• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.49-57
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• 2007

Using the idea of degree of openness and degree of nonopenness, Coker and Demirci [5] defined intuitionistic fuzzy topological spaces in Sostak's sense as a generalization of smooth topological spaces and intuitionistic fuzzy topological spaces. M. N. Mukherjee and S. P. Sinha [10] introduced the concept of fuzzy irresolute maps on Chang's fuzzy topological spaces. In this paper, we introduce the concepts of fuzzy (r,s)-irresolute, fuzzy (r,s)-presemiopen, fuzzy almost (r,s)-open, and fuzzy weakly (r,s)-continuous maps on intuitionistic fuzzy topological spaces in Sostak's sense. Using the notions of fuzzy (r,s)-neighborhoods and fuzzy (r,s)-semineighborhoods of a given intuitionistic fuzzy points, characterizations of fuzzy (r,s)-irresolute maps are displayed. The relations among fuzzy (r,s)-irresolute maps, fuzzy (r,s)-continuous maps, fuzzy almost (r,s)-continuous maps, and fuzzy weakly (r,s)-cotinuous maps are discussed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.331-336
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• 1998

A systematic design method for PDC(Parallel Distributed Compensation)-type continuous time Takagi-Sugeno(T-S in short) fuzzy control systems which have inaccessible states is developed in this paper. Reduced-dimensional fuzzy state estimator is introduced from existing T-S fuzzy model using the PDC structure of Wang et al. [1] LMI(Linear Matrix Inequalities) problems which represent the stabililty of the reduced-dimensional fuzzy state estimator are derived. Pole placement constraints idea for each rules is adopted to determine the estimator gains and they are also revealed as LMI problems. these LMI problems are combined with Joh et al's [7][8] LMI problems for PDC -type continuous time T-S fuzzy controller design to yield a systematic design method for PDC -type continuous time T-S fuzzy control systems which have inaccessible states.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.26.5-26
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• 2001

This paper proposes a new approach to identifying the unknown parameters of continuous LTI systems. For parameter identification in continuous-time systems, the Linear Integral Filter (LIF) method generally has been used in the beginning. Especially, one of the most efficient LIF methods in the literature is to use a weighting function satisfying specific three constraints. In high order systems, even though the weighting function satisfies the three constraints, it is impossible to identify the exact parameters of the systems because of information loss arising from a great amount of magnitude differences among the weighting function and its high-order derivatives. This paper, using an LMI technique, shows the limitation in designing the weighting function of the existing methods, and ...

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.3
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• pp.220-226
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• 2002

In this paper, we develop the intelligent digitally redesigned fuzzy controller for nonlinear systems. Takagi-Sugeno (TS) fuzzy model is used to model the nonlinear systems and a continuous-time fuzzy-model-based controller is designed based on the extended parallel-distributed-compensation(EPDC) method . The digital controllers are determined from existing analogue controllers. The proposed method provides an accurate and effective method for digital control of continuous-time nonlinear systems and enables us to efficiently implement a digital controller via the pre-determined continuous-time 75 fuzzy-model-based controller. We have applied the proposed method to the duffing forced oscillation system to show the effectiveness and feasibility of the proposed method.

• Structural Engineering and Mechanics
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• v.11 no.5
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• pp.469-484
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• 2001

A new beam system comprising two cantilever stems and an interspan composite beam has been developed and its design philosophy is described in this paper. The system provides the equivalent of a semi-continuous beam without the requirement to calculate the moment rotation capacity of the beam-to-column connection. The economy of braced frames using the system has been investigated and compared with simple, continuous or semi-rigid systems. It is shown that the costs of the proposed system are similar to the semi-rigid system and cheaper than both the simply supported and rigid beam systems. Two tests have been carried out on 6 meter span beams, which also incorporated an asymmetric flange steel section. The behaviour of the system is presented and the test results are compared with those obtained from the theory.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.177-180
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• 1996

The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closed-loop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1883-1887
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• 1991

Identification theory for linear discrete system has been presented by a great many reference, but research works for identification of continuous-time system are less than preceding identification. In fact, a great man), systems for engineering are continuous-time systems, hence, research for identification of continuous-time system has important meaning. This paper offers the following results: 1. Corresponding relations for the parameters of continuous-time model and discrete model may be shown, when single input-output system has general characteristic roots. 2. To do identification of single variable continuity linear system with stability constraints from samples of input-output data, it is necessary to use optimization with stability constraints. 3. Main results of this paper may be explained by a simple example.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.558-563
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• 1992

In this paper an identification of nonlinear continuous systems by using neural network is considered. The nonlinear continuous system is identified by two steps. At first, a linear approximate model of the continuous system with nonlinearity is obtained by IIR filtering approach. Then the modeling error due to the nonlinearity is reduced by a neural network compensator. The teaching signals to train the neural network is gotten by smoothing the measurement data corrupted by noise. An illustrative example is given to demonstrate the effectiveness of the proposed approach.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1055-1059
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• 1990

This paper proposed a predictive tracking controller for the continuous-time systems by using the receding horizon concept in the optimal tracking control. This controller is the continuous-time version of the previous RHTC (Receding Horizon Tracking Control) for the discrete-time state space models. The problems in implementing the feedforward part of this controller is discussed and a approximate method of implementing this controller is presented. This approximate method utilizes the information of the command signals on the receding horizon and has simple constant feedback and feedforward gain. To perform the offset free control, the integral action is included in the continuous time RHTC. By simulation it is shown that the proposed method gives better performance than the conventional steady state tracking control.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.506-508
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• 1998

In this paper, the optimal digital redesign is studied within the framework of fuzzy systems and dual-rate sampling control theory. An equivalent fast-rate discrete-time state-space model of the continuous-time system is constructed by using fuzzy inference systems. To obtain the optimal feedback gains developed in the continuous-time system, the constructed fuzzy system is converted into a continuous-time system. The developed continuous-time control law is converted into an equivalent slow-rate digital control law using the proposed digital redesign method. The digital redesign technique using a fuzzy model is employed to simulate the inverted pendulum dynamics.