• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1732-1733
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• 2011

This paper presents observer-based controller design for interval type-2 fuzzy system with staircase membership approximation. In type-2 fuzzy case, membership function is itself fuzzy set itself. Thus, type-2 fuzzy system can deal with parametric uncertainties of nonlinear system by capturing the uncertainties in membership function. Likewise, stabilization condition of type-2 fuzzy system is derived from quadratic Lyapunov function, and it goes to linear matrix inequality. Furthermore, in this paper, to relax the conservativeness of stabilization condition, staircase membership function approximating method is applied. Observer-based control method is adopted to control system which has some unmeasurable states. To prove suitability of our proposed method, numerical example is presented.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.498-503
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• 1993

In this paper, a robust and reliable H$_{\infty}$ control problem is considered for linear uncertain systems with time-varying norm-bounded uncertainty in the state matrix, which performs well despite of actuator outages. Using linear static state feedback and the quadratic stabilization with H$_{\infty}$-norm bound, a robust and reliable H$_{\infty}$ controller is obtained that stabilizes the plant and guarantees an H$_{\infty}$-norm bound constraint on disturbance attenuation for all admissible uncertainties and normal state as well as faulty state of actuators. It provides a sufficient condition for robust and reliable stabilization with H$_{\infty}$-norm bound. Reliability is guaranteed provided actuator outages only occur within a prespecified subset of actuators.tors.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.543-552
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• 1994

This paper presents a decentralized quadratic regulation architecture with feedforward neural networks for the control problem of complex systems. In this method, the decentralized technique was used to treat several simple subsystems instead of a full complex system in order to reduce training time of neural networks, and the neural networks' nonlinear mapping ability is exploited to handle the nonlinear interaction variables between subsystems. The decentralized regulating architecture is composed of local neuro-controllers, local neuro-identifiers and an overall interaction neuro-identifier. With the interaction neuro-identifier that catches interaction characteristics, a local neuro-identifier is trained to simulate a subsystem dynamics. A local neuro-controller is trained to learn how to control the subsystem by using generalized Backprogation Through Time(BTT) algorithm. The proposed neural network based decentralized regulating scheme is applied in the power System Stabilization(PSS) control problem for an imterconnected power system, and compared with that by a conventional centralized LQ regulator for the power system.

• Current Optics and Photonics
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• v.5 no.3
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• pp.289-297
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• 2021

We describe a comb-mode resolving spectroscopic technique by direct time-domain phase correction of unstable interferograms obtained from loosely locked two femtosecond lasers. A low-cost continuous wave laser and conventional repetition rate stabilization method were exploited for locking carrier and envelope phase of interferograms, respectively. We intentionally set the servo control at low bandwidth, resulting in severe interferograms' fluctuation to demonstrate the capability of the proposed correction method. The envelope phase of each interferogram was estimated by a quadratic fit of carrier peaks to correct timing fluctuation of interferograms in the time domain. After envelope phase correction on individual interferograms, we successfully demonstrated 1 Hz linewidth of RF comb-mode over 200 GHz optical spectral-bandwidth with 10-times signal-to-noise ratio (SNR) enhancement compared to the spectrum without correction. Besides, the group delay difference between two femtosecond pulses is successfully estimated through a linear slope of phase information.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.14-25
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• 2012

Recently, the application and installation of the pod propeller to the cruise ship is dramatically increased. It is because pod propulsion system allows a lot of flexibility in design of the internal arrangement of a ship. To reflect this trend, many researches have conducted to use the pod propeller for the roll stabilization of a ship. In the paper, a roll stabilization controller is designed by using fins and pod propellers as the control actuators for cruise ships. Two kinds of control algorithms are adopted for the roll control system; LQR (Linear Quadratic Regulator) algorithm and frequency-weighted LQR algorithm. Through the numerical simulation, the effect of the turning rate of the pod propeller on the roll control system is analyzed. Analysis of the simulation results indicated that the turning rate of the pod propellers is one of the important parameters which give the significant effects on the roll stabilization.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.433-436
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• 1990

An optimal Stabilization technique for a bilinear in duction model is introduced. This technique includes to o parts; the one is an stabilization control using Lyap unov Function which has the form of a sum of linear and quadratic function of the state variables, and the other is an optimal control using the performance index which depends on the choice of the elements of the Ly apunov matrices concerning both the state variables and the input variables. Therefore, induction motor is drived with the shorter transient time of the state variables and with the smaller overshoot of the ones, simulation results are obtained from a digital computer. Experimental ones are obtained from implementation of the optimizing controller using 8086 microprocessor kits and analog circuits are compared.

• Journal of the Korean Mathematical Society
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• v.52 no.3
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• pp.567-586
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• 2015

In this paper, we study optimal control problems for parabolic hemivariational inequalities of dynamic elasticity and investigate the continuity of the solution mapping from the given initial value and control data to trajectories. We show the existence of an optimal control which minimizes the quadratic cost function and establish the necessary conditions of optimality of an optimal control for various observation cases.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.742-746
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• 1992

This paper proposes a new linear robust state feedback controller for the linear discrete time systems which have uncertainties in the state and input matrices. The uncertainties need not satisfy the matching conditions, but only their bounds are needed to be known. The proposed controller is derived from the linear quadratic game problem, which solution is obtained via the modified algebraic Riccati equation. The controller guarantees the robust performance bound. The bound of the solution and the condition of the uncertainties, which can stabilize the uncertain system are explored.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.506-514
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• 2008

This paper presents an intelligent model; named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.30-39
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• 2002

This paper deals with the design of a robust LQC/LTR (Linear Quadratic Gaussian with Loop Transfer Recovery) controller of the TCSC for the power system oscillation damping enhancement. Designing LQG/LTR controller involves several design parameter adjustment processes for performance improvement. this paper proposes a systematic design parameter adjustment procedure which is suitable for robust multi-monde stabilization. The designed controller is verified by nonlinear power system simulation, which shows that the controller is effective for damping power system oscillations.