• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.47-52
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• 1994

In industrial multivariable plants, it is often the case that all of plant outputs are measured not simultaneously, but seriallu. While Reference 1 proposed a special type of observer (referred to as "serial-sampling" type obserrversL. which was provento be very effective in this situation, it alsopointed out that the observer may have some minor problems in case of practical applications. In this paper, it isshown that these kind of problems can be resolved by proving the existence of the solution of the simultaneous equations (35) of Reference 1.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1856-1857
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• 2011

Induction motor is nonlinear multivariable system. It is not easy to control precisely. Usually Induction motor need linearized model in order to make it easy to control. In this paper, linearized model of nonlinear model in induction motor can change by using TS Fuzzy Identification.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1298-1301
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• 2007

The problem of designing dynamic output feedback sliding mode controllers for uncertain multivariable linear systems is considered. Using linear matrix inequalities(LMIs), a feasibility condition for the design problem is derived. Explicit fomulas of the gain matrices of a full order output feedback sliding mode controller in terms of the solution matrices of the LMI condition is given. A simple LMI-based algorithm for designing output feedback sliding mode controllers is also given. Finally, numerical design examples are given to show the effectiveness of the proposed method.

• Journal of the Korean Mathematical Society
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• v.46 no.6
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• pp.1277-1292
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• 2009

This paper is an attempt to stress the usefulness of the multivariable special functions. In this paper, we derive generating relations involving 3-variable 2-parameter Tricomi functions by using Lie-algebraic techniques. Further we derive certain new and known generating relations involving other forms of Tricomi and Bessel functions as applications.

• Bulletin of the Korean Mathematical Society
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• v.57 no.2
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• pp.521-533
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• 2020

In this paper, we compute the Bergman kernel for Ω_p,q,r = {(z, z', w) ∈ ℂ² × Δ : |z|^2p < (1 - |z'|^2q)(1 - |w|²)^r}, where p, q, r > 0 in terms of multivariable hypergeometric series. As a consequence, we obtain the behavior of K_Ωp,q,r (z, 0, 0; z, 0, 0) when (z, 0, 0) approaches to the boundary of Ω_p,q,r.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.491-497
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• 1993

In MIMO design, input and output units are different from each other. By this reason, the effect of larger units to smaller one is not trivial and there is no method of proper scaling, optimal scaling. In this paper, robust stability of MIMO LQG/LTR design are analised when the plnat inputs and outputs are scalled. The upper bound of model error to guarantee the robust stability is obtained, and gain margin and phase margins are computed with respect to scalling matrices.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.577-580
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• 1996

LQ-servo is a stability-robustness guaranteed multivariable controller design method based on the LQR structure to improve command following performance with output feedback. In this paper, a new type of PI controller based on LQ-servo is introduced. Then, Command following performance is improved using the limiting behavior of the control gain and weighting factors on the low frequency part of design parameter Q that is the state weighting matrix in the cost function.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.11
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• pp.511-518
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• 1986

An algorithm for block-decomposition of a linear, time-invariant, discrete large-scale systems is presented, based upon the matrix sign function on Z-plane. The block-decomposition is performed by defining a reference circle, a circular stripe and projection operators. Simulation study shows that the presented algorithm is very useful for multivariable control system's analysis and design.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.687-692
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• 1991

To reduce the complexity in constructing a fuzzy logic controller of multivariable systems, three major methods are presented. One is the method of constructing single-input-single-output fuzzy logic controllers after decoupling the target system. Another is the method of using fuzzy relation matrices which indicate the relation between each input and output. The other is the method of using the hierarchically classified inputs which dominantly influence one output than other inputs. Using the last two methods, simulation results of fuzzy logic controller implemented on 160MW boiler-turbine plant model are also shown.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.878-883
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• 1991

In this paper, we propose the fuzzy-neural controller which is fuzzy controller with learning ability of neural network. The neural network in this controller is same as the membership function in current fuzzy controller and a parts of inference rules. And, it can be easily extend the control algorithm to multivariable systems. We can show effectiveness of the control algorithm through experiment of the inverted pendulum system.