• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.296-298
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• 1993

The performance of MODEL-BASED controller is influenced by model parameter errors and velocity measurement errors. To reduce this errors, Control methods by parameter adaptation and velocity estimation are studied. But because these controller has complex construction and need much computation time, the implementation of single processor system is difficult. This paper proposes a control scheme which combines an adaptive control law with a sliding observer using transputer network.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.384-386
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• 2009

This paper introduces an effectively optimized Fuzzy model identification by means of complex and nonlinear system applying PSO algorithm. In other words, we use PSO(Particle Swarm Optimization) for identification of Fuzzy model structure and parameter. PSO is an algorithm that follows a collaborative population-based search model. Each particle of swarm flies around in a multidimensional search space looking for the optimal solution. Then, Particles adjust their position according to their own and their neighboring-particles experience. This paper identifies the premise part parameters and the consequence structures that have many effects on Fuzzy system based on PSO. In the premise parts of the rules, we use triangular. Finally we evaluate the Fuzzy model that is widely used in the standard model of gas data and sew data.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1210-1215
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• 1990

This paper deals with the fault diagnosis problem in uncertain linear systems having undermodelling, linearization errors and noise inputs. The new approach proposed in this paper uses an appropriate test variable and the difference between system parameters which are estimated by the least squares method to locate the fault. The singular value decomposion is used to decouple the correlation between the estimated system parameters and to observe the trend of parameter changes. Some simulations applied to aircraft ergines show good allocation of the fault even though the system model has significant uncertainties. The feature of the approach is to diagnose the uncertain system through simple parameter operations and not to need complex calculations in the diagnosis procedure as compared with other methods.

• Journal of the Korean Mathematical Society
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• v.48 no.5
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• pp.913-926
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• 2011

The family of q-Laguerre polynomials $\{L_n^{(\alpha)}({\cdot};q)\}_{n=0}^{\infty}$ is usually defined for 0 < q < 1 and ${\alpha}$ > -1. We extend this family to a new one in which arbitrary complex values of the parameter ${\alpha}$ are allowed. These so-called generalized q-Laguerre polynomials fulfil the same three term recurrence relation as the original ones, but when the parameter ${\alpha}$ is a negative integer, no orthogonality property can be deduced from Favard's theorem. In this work we introduce non-standard inner products involving q-derivatives with respect to which the generalized q-Laguerre polynomials $\{L_n^{(-N)}({\cdot};q)\}_{n=0}^{\infty}$, for positive integers N, become orthogonal.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.301-305
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• 1996

$\mu$ theory can handle the parametric uncertainty and produces more non-conservative controller than H$_{\infty}$ control theory. However an existing solution of the theory, D-K iteration, creates a controller of huge order and cannot handle the real or mixed real-complex perturbation sets. In this paper, we use genetic algorithms to solve these problems of the D-K iteration method. The Youla parameterization is used to obtain all stabilizing controllers and the genetic algorithms determines the values of the state feedback gain, the observer gain, and Q parameter to minimize $\mu$, the structured singular value, of given system. From an example, we show that this method produces lower order controller which controls a real parameter-perturbed plant than D-K iteration method.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.590-593
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• 2009

Tidal current power system is one of ocean renewable energies that can minimize the environmental impact with many advantages compared to other energy sources. Not like others, the produced energy can be precisely predicted without weather conditions and also the operation rate is very high. To convert the current into power, the first device encountered to the incoming flow is the rotor that can transform into rotational energy. The performance of rotor can be determined by various design parameters including numbers of blade, sectional shape, diameter, and etc. The stream lines near the rotating rotor is very complex and the interference effects around the system is also difficult to predict. This paper introduces the experiment of rotor performance and also the effect of design parameter on the performance of HAT rotor by CFD.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.05a
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• pp.175-180
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• 1999

Generally, When we measure of object 3D surfaces with phase shifting shadow moire method, it is use of optical system consist of light source, grating, and ccd camera. At this time, it is important parameter that vertical distance of grating and camera, grating and light source, and horizontal distance of camera and light source. When use camera consist of complex lens vertical distance of grating and camera is unknown parameter. From this cause equivalent wave length of moire fringe is uncertain. In this study, We exactly obtain a vertical distance of grating and camera so improve on measurement accuracy.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.381-383
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• 2015

MOdified Newtonian Dynamics (MOND) is an alternative to the dark matter paradigm. MOND asserts that when the magnitude of acceleration is smaller than the acceleration parameter $a_0$, the response of the system to gravity is stronger (larger acceleration) than the one given by Newtonian dynamics. The current value of $a_0$ is obtained mostly by observations of spiral galaxies (rotation curves and the Tully-Fisher relation). We attempt to estimate $a_0$ from the dynamics of elliptical galaxies. We seek elliptical galaxies that act as the lens of gravitational lensing systems and have velocity dispersion data available. We analysed 65 Einstein rings from the Sloan Len ACS survey (SLACS). The mass estimates from gravitation lensing and velocity dispersion agree well with each other, and are consistent with the estimates from population synthesis with a Salpeter IMF. The value of $a_0$ obtained from this analysis agrees with the current value.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.153-158
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• 1995

In this paper, A new design method of fuzzy modeling is presented for the model identification of nonlinear complex systems. The proposed fuzzy GMDH modeling implements system structure and parameter identification using GMDH(Group Method of Data Handling) algorithm and linguistic fuzzy implication rules from input and output data of processes. In order to identify premise structure and parameter of fuzzy implication rules, GMDH algorithm and fuzzy reasoning method are used and the least square method is utilized for the identification of optimum consequence parameters. Time series data for gas furnaceare those for sewage treatment process are used for the purpose of evaluating the performance of the proposed fuzzy GMDH modeling. The results show that the proposed method can produce the fuzzy model with higher accuracy than other works achieved previously.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2929-2931
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• 1999

In this paper, an adaptive fuzzy inference and HCM(Hard C-Means) clustering method are used for on-line fuzzy modeling of nonlinear and complex system. Here HCM clustering method is utilized for determining the initial parameter of membership function of fuzzy premise rules and also avoiding overflow phenomenon during the identification of consequence parameters. To obtain the on-line model structure of fuzzy systems. we use the recursive least square method for the consequent parameter identification. And the proposed on-line identification algorithm is carried out and is evaluated for sewage treatment process system.