• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.147-149
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• 2004

There are no authentic solutions in a face region extraction problem though it is an important part of pattern recognition and has diverse application fields. It is not easy to develop the facial region extraction algorithm because the facial image is very sensitive according to age, sex, and illumination. In this paper, to solve these difficulties, a fuzzy color filer based on the facial region extraction algorithm is proposed. The fuzzy color filter makes the robust facial region extraction enable by modeling the skin color. Especially, it is robust in facial region extraction with various illuminations. In addition, to identify the fuzzy color filter, a linear matrix inequality(LMI) optimization method is used. Finally, the simulation result is given to confirm the superiority of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.893-895
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• 2005

We represent an efficient intelligent digital redesign method for a Takagi-Sugeno (T-S) fuzzy system. intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows to matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality (LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.220-222
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• 2006

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 the 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 lineal operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, 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 the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a T-S fuzzy model for the chaotic Lorentz system is used as an example to guarantee the stability and effectiveness of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.3105-3107
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• 2005

We represent an efficient intelligent digital redesign method for a Takagi-Sugeno (T-S) fuzzy system. Intelligent digital redesign means that an existing analog fuzzy-model-based controller converts to equivalent digital counter part in the sense of state-matching. The proposed method performs previous work, moreover, it allows to matching the states of the overall closed-loop T-S fuzzy system with the predesigned analog fuzzy-model-based controller. And the problem of stability represent convex optimization problem and cast into linear matrix inequality (LMI) framework. This method applies to the helicopter systems which are the nonlinear plant and determine the feasibility and effectiveness of the proposed method.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.3
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• pp.139-145
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• 2001

In this paper, we consider the H$_2$(or guaranteed cost control) and H$_{\infty}$ controller design methods for singular(or descriptor) systems with input time delay. Also, a mixed H$_2$and H$_{\infty}$ controller design algorithm is treated by combination of the proposed H$_2$and H$_{\infty}$ controller design method. The sufficient conditions for the existence of controllers and controller design methods are introduced at each Lemma and Theorem. Furthermore, we present optimization problems to get the upper bound of performance measures. The proposed methods are checked by examples.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.163-168
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• 2000

The problems of mixed $H_2/H_{\infty}$ filtering design fer continuous and discrete time linear systems with time delay are investigated. The main purpose is to design a stable mixed $H_2/H_{\infty}$ filter which minimizes the H$_2$Performance measure satisfying a prescribed H$_{\infty}$ norm bound on the closed loop system in continuous-time case and discrete-time case, respectively. The sufficient conditions of existence of filter, the mixed $H_2/H_{\infty}$ filter design method, and the upper bound of performance measure are proposed by LMI(linear matrix inequality) techniques in terms of all finding variables. Also, we present optimization problems in order to get the optimal mixed $H_2/H_{\infty}$ filter in continuous and discrete time case, respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.685-689
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• 2005

In this paper, we consider a robust output feedback model predictive controller(MPC) design for Wiener model. Nonlinearities that couldn't be represented in static nonlinearity block of Wiener model are regarded as uncertainties in linear block. An dynamic output feedback controller design method is presented for Wiener MPC. According to MPC algorithm, the control law is computed based on linear matrix inequality(LMI)at each sampling time by solving convex optimization. Also, a new parameter dependent Lyapunov function is proposed to get a less conservative condition. The results are illustrated with numerical example.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.365-370
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• 2007

This paper studies an automation problem of a heating, a ventilating, and an air conditioning (HVAC) for the development of smart space. The HVAC system is described by the fuzzy system for the stability analysis and the controller design. The linear matrix inequalities (LMIs) conditions are derived for the stabilization problem of the closed-loop system under the analog control. Also, it is required to digitally redesign the pre-designed the analog HVAC control system in order to accomplish the remote control via web. It is shown the this digital redesign problem can be converted to the convex optimization problem with the LMI constraints. An example is provided to show the effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.423-431
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• 2000

In this paper, the effect of computing time-delay in the real-time digital fuzzy control systems is investigated and the design methodology of a real-time digital fuzzy controller(DFC) to overcome the problems caused by it is presented. We propose the fuzzy feedback controller whose output is delayed with unit sampling period. The analysis and the design problem considering computing time-delay is very easy because the proposed controller is syncronized with the sampling time. The stabilization problem of the digital fuzzy control system is solved by the linear matrix inequality(LMI) theory. Convex optimization techniques are utilized to find the stable feedback gains and a common positive definite matrix P for the designed fuzzy control system Furthermore, we develop a real-time fuzzy control system for backing up a computer-simulated truck-trailer with the consideration of the computing time-delay. By using the proposed method, we design a DFC which guarantees the stability of the real time digital fuzzy control system in the presence of computing time-delay.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1220-1223
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• 2002

In this paper, numerical robust stability analysis method and its design are presented. L$_2$robust stability of the fuzzy system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linarization control gains is proposed.