• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2354-2356
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• 1998

We present a fuzzy model for a robot manipulator and use the model to decide the PD gains of a stiffness controller. Force control applications are extremely difficult to accomplish with such a stiffness robot because robot itself, unknown environment. So we identify a fuzzy model by using Hough transform. We present a method of design of the PD gains of the stiffness controller. We aim at controlling the end-effecor force in the face of uncertainty on the surface stillness. simulation results verify the effectiveness of the proposed strategy.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.341-344
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• 2007

This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization of chaotic systems. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. This improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived and the stability of the proposed observer is analyzed. Some simulation result is given to present the validity of theoretical derivations and the performance of the proposed observer.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.1
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• pp.34-39
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• 2013

This paper proposes the implementation of robust fuzzy controller for designing intelligent wind farm and mitiagating the fluctuation of wind power generator. The existing researches are limited to individual wind turbine with variable speed so that it is necessary to study the multi-agent wind turbine power system. The scopes of these studies include from the arrangements of each power turbine to the control algorithms for the wind farm. For solving these problems, we introduce the composition of intelligent wind farm and use the T-S (Takagi-Sugeno) fuzzy model which is suitable for designing fuzzy controller. The control object in wind farm enables the minimizing the fluctuation of wind power generator. Simulation results for wind fram which is modelled as mathematically are demonstrated to visualize the feasibility of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.374-378
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• 2003

A new discrete-time fuzzy output feedback control method for nonlinear systems with unknown time-delay is proposed. Ma et al. proposed an analysis and design method of fuzzy controller and observer and Cao et al. extend this result to be applicable fir the nonlinear systems with known time-delay. For the case of unknown time-delay, we derive the sufficient condition f3r the asymptotic stability of the equilibrium Point by applying Lyapunov-Krasovskii theorem and convert this condition into the LMI problem.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.600-602
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• 1996

The purpose of this paper is to develop a new maximum power point tracking(MPPT) using fuzzy set theory for air conditioning system. Fuzzy algorithm based on linguistic rules describing the operator's control strategy is applied to control step-up chopper for MPPT. Fuzzy algorithm is applied to control boost MPPT converter by temperature compensation effect with 8 bit single chip 8051 microcontroller. In this paper, temperature compensation(Becom Transducer : pf-T type) range is $-40^{\circ}C{\sim}+100^{\circ}C$.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.206-208
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• 1997

This paper presents a design of self_tuning fuzzy logic controller using Genetic Algorithms for power system stabilization. FPSS(Fuzzy Logic Power System Stabilized is applied to the KERI(Korea Electric Research Int.) power system simulator so that its efficiency can be investigated in real time control. Genetic Algorithms are used to determine fuzzy membership functions. Experiment results show the better performances with FPSS in comparison to no PSS.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1783-1784
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• 2008

This paper presents a novel control technique to deal with networked control systems with neutral timedelay, which is known to highly degrade the control performance of the controlled system. The stability analysis and design method for a sampled-data fuzzy controller for discrete networked control systems (NCS). The neutral time-delay and sampling activity will complicate the NCS. And it make the stability analysis much more difficult than that for a continuous-time NCS. Based on the fuzzy control approach, linear matrix inequality (LMI)-based stability conditions are derived to guarantee the neutral T-S fuzzy system stability. The simulation results and practical experiments illustrate that the proposed controller design is realistic.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.353-353
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• 2000

To control a light weight flexible manipulator, a composite fuzzy controller is proposed. The controller is designed based on two time scaled models. A singular perturbation technique is applied for deriving the models. The proposed controller, however, does not use the complex equilibrium manifold equations, which are usually needed in the controller based on the two time scaled models. The controller for a slow sub-model and a fast sub-model are T-S type fuzzy controllers, which use 3 linguistic variables for each sub-model. A step trajectory is used in simulations as a reference trajectory of joint motions. The results of simulations with the proposed controller show excellent damping of flexible motions compared to a controller with derivative control of flexible motions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.6-9
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• 2006

A generalized net is used to construct a model which describes the process of evaluation of the problems solved by students. The model utilizes the theory of intuitionistic fuzzy sets. The model can be used to simulate some processes, related to estimation of students' background.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.12
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• pp.68-74
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• 1991

This paper proposes a HMM model based on fuzzy, as a method on the speech recognition of speaker-independent. In this recognition method, multi-observation sequences which give proper probabilities by fuzzy rule according to order of short distance from VQ codebook are obtained. Thereafter, the HMM model using this multi-observation sequences is generated, and in case of recognition, a word that has the most highest probability is selected as a recognized word. The vocabularies for recognition experiment are 146 DDD are names, and the feature parameter is 10S0thT LPC cepstrum coefficients. Besides the speech recognition experiments of proposed model, for comparison with it, we perform the experiments by DP, MSVQ and general HMM under same condition and data. Through the experiment results, it is proved that HMM model using fuzzy proposed in this paper is superior to DP method, MSVQ and general HMM model in recognition rate and computational time.