• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.58-66
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• 1999

The problem of feedback linearization of SISO nonlinear systems with outputs has been solved by Lee et al. [5]. Also, Cheng et al. [1] have found the necessary and sufficient conditions for MIMO systems, which are, however, uncheckable. In this paper, we consider the MIMO nonlinear systems and obtain the verifiable necessary and sufficient conditions for feedback linearization with output.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.35-43
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• 2000

Time Delay Control (TDC) method was proposed as a promising technique in the robust control area, where the plants have unknown dynamics with parameter variations and substantial disturbances are present. In this paper, based on the concepts of TDC, author propose a model reference control method for input/output model. The stability and robustness of the closed system has been analyzed for a class of linear time invarient (LTI) system. Then, in a simulation study, author's design method has been applied to a second order system, the result of which confirmed that the proposed control method performs satisfactorily as predicted.

• Journal of the Korean Vacuum Society
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• v.2 no.3
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• pp.374-383
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• 1993

필라멘트와 Si 기판 사이의 기전력을 20, 80, 140, 200V로 증가시키면서 EACVD에 의하여 성장된 다이아몬드 박막에 대하여 다이아몬드/Si 계면분석 및 계면강도를 측정하였다. 주사형전자현미경(SEM), 고분해능투과형전자현미경(HRTEM), 오제이전자분석기(AES)에 의해 계면상태를 분석한 결과, 기전력 증가에 따라 활성탄화수소 이온(CmHn-)에너지가 증가되어져 CmHn-이 Siso로 침투(Impringement)가 증가되고 침투된 높은 에너지의 CmHn-이 Si과 화학결합하여 생성되는 SiC층 깊이 및 농도 분포도 증가된다. 풀 시험(Pull test)에 의한 계면강도 측정 결과, SiC층 깊이 및 농도분포가 증가할수록 계면강도가 증가하였다. 관찰된 파면과 파면의 X-선 메핑 결과 및 HRTEM과 AES에 의한 분석 결과, 기전력 증가에 따라 공극율이 적고 치밀한 다이아몬드 박막이 성장된다. 그리고 생성되는 SiC층 농도 및 깊이 분포가 증가함에 따라 다이아몬드/Si 계면이 강화되고, 상대적으로 파괴는 다이아몬드/Si 계면이 아닌 SiC층이나 Si 내부에서 발생된다. 결국, 기전력을 증가하여 활성탄화수소이온의 에너지를 증가함으로써 계면강도가 우수하며 공극율이 매우 적고 치밀한 다이아몬드 박막을 성장할 수 있다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.52-57
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• 2006

In this paper, we have proposed a new adaptive fuzzy control algorithm based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter approximation error is proved. Unlike the existing feedback linearization based methods, the proposed algorithm can guarantee the global stability in the presence of the singularity in the inverse dynamics of the plant. The performance of the proposed algorithm is demonstrated through the problem of balancing and swing-up of an inverted pendulum on a cart.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.697-700
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• 2005

An adaptive fuzzy sliding-mode controller (SMC) for uncertain or ill-defined single-input single-output (SISO) nonaffine nonlinear systems is proposed. By using the universal approximation property of the fuzzy logic system (FLS), it is tuned on-line to cancel the unknown system nonlinearity. We adopt a self-structuring FLS to guarantee global stability of the closed-loop system rather than semi=global boundedness. The control and adaptive laws are derived so that the estimated fuzzy parameters are bounded and the sliding condition is satisfied.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.185-189
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• 1998

This paper addresses analysis and design of a fuzzy model-based-controller for the control of uncertain SISO nonlinear systems. In the design procedure, we represent the nonlinear system by using a Takagi-Sugeno fuzzy model and construct a global fuzzy logic controller via parallel distributed compensation and sliding mode control. Unlike other parallel distributed controllers, this globally stable fuzzy controller is designed without finding a common positive definite matrix for a set of Lyapunov equations, and has good tracking performance. The stability analysis is conducted not for the fuzzy model but for the real underlying nonlinear system. Furthermore, the proposed method can be applied to partially known uncertain nonlinear systems. A numerical simulation is performed for the control of an inverted pendulum, to show the effectiveness and feasibility of the proposed fuzzy control method.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.32-42
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• 2001

In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.481-482
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• 2007

This paper demonstrates OFDM with adaptive modulation applied to Multiple-Input Multiple-Output (MIMO) systems. We apply an optimization algorithm to obtain a bit and power allocation for each subcarrier assuming instantaneous channel knowledge. The analysis and simulation is considered in two stages. The first stage involves the application of a variable-rate variable-power MQAM technique for a Single-Input Single-Output(SISO) OFDM system. This is compared with the performance of fixed OFDM transmission where a constant rate is applied to each subcarrier. The second stage applies adaptive modulation to a general MIMO system by making use of the Singular Value Decomposition to separate the MIMO channel into parallel subchannels. For a two-input antenna, two-output antenna system, the performance is compared with the performance of a system using selection diversity at the transmitter and maximal ratio combining at the receiver.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.8
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• pp.462-470
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• 2003

This paper presents an algorithm of identifying parametric uncertainty by way of an interval model. For a given set of frequency response data from an uncertain linear SISO system of which the upper and the lower bounds of both magnitude and phase responses are represented, the proposed algorithm consists of two main parts: first, the nominal model is identified by using Least Square Estimation (LSE), and then an interval model is constructed by expanding the extremal properties of interval systems, so that tightly enclose the given envelopes within those of interval model. Two numerical examples are given to demonstrate and verify the developed algorithm. The identified interval model can be used for evaluating the worst case performance and stability margins against parametric uncertainty by using some extremal properties on interval systems.