• Journal of KSNVE
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• v.6 no.4
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• pp.521-528
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• 1996

Recently, higher speed optical disk drives including computer CD-ROM drives tend to be increasingly demanded to read or write the enormous volume of digital data. To this end, both structure and controller designs of the optical pick-ups should be improved concurrently. In this paper, the pick-up during auto-focusing motion is mathematically modelled retaining all its peculiar features. The model turns out a linear time invariant system suitable for a control design namedH${\infty}$ which ensures robust stability in the presence of system uncertainties. Numerical simulations are performed to demonstrate the robustness with appropriate performance specifications being satisfied. In addition, as the implementation issue of it, procedures of temporal discretization as well as model reduction of the controller are also addressed.

• 한국전산유체공학회:학술대회논문집
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• 2011.05a
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• pp.458-464
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• 2011

A new method identifies coupled fluid-structure system with a reduced set of state variables is presented. Assuming that the structural model is known a priori either from an analysis or a test and using linear transformations between structural and aeroelastic states, it is possible to deduce aerodynamic information from sampled time histories of the aeroelastic system. More specifically given a finite set of structural modes the method extracts generalized aerodynamic force matrix corresponding to these mode shapes. Once the aerodynamic forces are known, an aeroelastic reduced-order model can be constructed in discrete-time, state-space format by coupling the structural model and the aerodynamic system. The resulting reduced-order model is suitable for constant Mach, varying density analysis.

• Journal of IKEEE
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• v.23 no.4
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• pp.1265-1272
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• 2019

We analyze the robustness of the existing predictor feedback controller for discrete-time linear systems with constant input delays against the structured model uncertainty. By modeling the constant input delay with a first-order PdE (Partial difference Equation), we replace the input delay with the PdE states. By applying a backstepping transformation, we build a target system that enables to construct an explicit Lyapunov function. Constructing the explicit Lyapunov function that covers the entire state variables, we prove the existence of an allowable maximum size of the structured model uncertainty to maintain stability and establish the robustness of the predictor feedback controller. The numerical example demonstrates that the stability of closed-loop system is maintained in the presence of the structured model uncertainty, and verifies the robustness of the predictor feedback controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.293-299
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• 2003

This paper discusses a design of intelligent controller with time delay for Internet-based remote control. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The Takagi-Sugeno (T-S) fuzzy system with uncertain input delay is utilized to represent nonlinear plant. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The robust stochastic stabilizibility of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). An experimental results is provided to visualize the feasibility of the proposed method.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2631-2633
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• 2005

In this paper, we propose a new discrete-time predictive current controller for a PMLSM(permanent magnet linear synchronous motor). The main objectives of the current controllers are that the measured stator current is tracked the command current value accurately and the transient interval is shorten as much as possible, in order to obtain high-performance of ac drive system. The conventional predictive current controller is hard to implement in full digital current controller since a finite calculation time causes a delay between the current sensing time and the time that take to apply the voltage to motor. A new control strategy is the scheme that gets the fast adaptation of transient current change, the fast transient response tracking. Moreover, the simulation results will be verified the improvements of predictive controller and accuracy of the current controller.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.1
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• pp.83-91
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• 1990

An adaptive observer which is applicable to discrete linear time invariant systems of ARMA type in the presence of noise is proposed. It first estimates the system parameters of the MA type by applying only the system input to the observer. Then it estimates the output which corresponds to the output of the system without any noise. This is a special case of Suzuki's adaptive observer. This estimated output is applied to Suzuki's adaptive observer to estimate the system parameters of ARMA type and the states. The proposed method can make the estimate errors of the system parameters sufficiently small even in the presence of noise in the system. It can also make the estimate errors of the states of the system sufficiently small when there is no process noise. These properties of the proposed adaptive observer is certified by computer simulation.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.285-290
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• 2007

In this paper, we presents robust digital redesign (DR) method for observer-based linear time-invariant (LTI) system. The term of DR involves converting an analog controller into an equivalent digital one by considering two condition: state-matching and stability. The design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed the uncertain parts of given observer-based system more precisely, When a sampling period is sufficiently small, the conversion of a analog structured uncertain system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs).

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.265-267
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• 2004

A blind separation problem in a multiple-input-multiple-output (MIMO) linear time-invariant (LTI) system with finite-alphabet inputs is considered. A discrete-time matrix equation model is used to describe the input-output relation of the system in order to make full use of the advantages of modern digital signal processing techniques. At first, ambiguity problem is investigated. Then, based on the results of the investigation, a new identifiability condition is proposed for the case of an input-data set which is widely used in digital communication. A probability bound such that an arbitrary input matrix satisfies the identifiability condition is derived. Finally, Monte-Carlo simulation is performed to demonstrate the validity of our suggestions.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.44-49
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• 1999

This paper presents a new T-S(Tae-Sugeno) fuzzy controller design method satisfying the output energy bound. Maximum output energy via a quadratic Lyapunov function to obtain the bound on output energy is derived. LMI(Linear Matrix Inequality) problems which satisfy an output energy bound for both of the continuous-time and discrete-time T-S fuzzy control system are also derived. Solving these LMIs simultaneously, we find a common symmetric positive definite matrix P which guarantees the global asymptotic stability of the system and stable feedback gains K's satisfying the output energy bound. A simple example demonstrates validity of the proposed design method.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.1-22
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• 1997

Learning control refers to controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented a theory of indirect decentralized learning control based on use of indirect adaptive control concepts employing simultaneous identification and control. This paper extends these results to apply to the indirect repetitive control problem in which a periodic (i.e., repetitive) command is given to a control system. Decentralized indirect repetitive control algorithms are presented that have guaranteed convergence to zero tracking error under very general conditions. The original motivation of the repetitive control and learning control fields was learning in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the desired trajectory. Decentralized repetitive control is natural for this application because the feedback control for link rotations is normally implemented in a decentralized manner, treating each link as if it is independent of the other links.