• Journal of KSNVE
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• v.9 no.1
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• pp.33-41
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• 1999

This paper presents a method of actively controlling the interior noise by a trim panel with hybrid feedforward-feedback control loop. The control technique is designed to minimize the vibration of panel whose motion is limited to that of a piston (out-of-plane motion). The hybrid controller consists of an adaptive feedforward controller in conjunction with a linear quadratic Gaussian (LQG) feedback controller. In order to maintain control performance of both persistent and transient disturbances, the feedback loop speeds up the adaptation rate of feedforward controller by improving damping capacity of secondary plant related with the adaptation rule. Numerical simulation and experimental result indicate that the hybrid controller is a more effective method for reducing the vibration of the panel (and therefore the interior noise) compared to using feedforward controller.

• Journal of Electrical Engineering and Technology
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• v.10 no.3
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• pp.925-934
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• 2015

This paper considers the robust controller design problem for a boost DC-DC converter. Based on the Takagi-Sugeno fuzzy model-based approach, a fuzzy controller as well as a fuzzy load conductance observer are designed. Sufficient conditions for the existence of the controller and the observer are derived using Linear Matrix Inequalities (LMIs). LMI parameterizations of the gain matrices are obtained. Additionally, LMI conditions for the existence of the fuzzy controller and the fuzzy load observer guaranteeing α-stability, quadratic performance are derived. The exponential stability of the augmented fuzzy observer-controller system is shown. It is also shown that the fuzzy load observer and the fuzzy controller can be designed independently. Finally, the effectiveness of the proposed method is verified via experimental and simulation results under various conditions.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.61-76
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• 2002

The robust non-fragile guaranteed cost control problem is studied in this paper for class of uncertain linear large-scale systems with time-varying delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-hounded arid time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound far all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost contrellers is 7iven in terms of the feasible solution to a certain LMI. Finally, in order to show the application of the proposed method, a numerical example is included.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1136-1141
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• 2004

This paper presents a control method for time-delay systems and verifies the performance of the designed control system via real experiments. Specifically, the control method is applied to a flexible-link system with time delays. The method combines time- and frequency-domain controllers: linear quadratic optimal controller (or LQR) and lag compensator. The LQR is used to stabilize the system in optimal fashion, whereas the lag compensator is used to compensate time-delay effects by increasing the delay margin of the system. With this methodology, the maximum allowable time delay can be increased significantly. The proposed method is simple but quite practical for time-delay system control as it is based on the conventional loop-shaping method, which gives practical insights on delay-phase relationship. Simulation and experiment results show that the method presented in this paper is feasible and practical.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.183-186
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• 2007

This Paper presents a solution to control the Brushless DC Motor(BLDCM) in Hard Disk Drive(HDD) using the Linear Quadratic Regulator(LQR). Generally, The speed of BLDCM in HDD is controlled by the lead angle control or the input voltage control using PAM(Pulse Amplitude Modulation) etc. These control methods have speed overshoot in speed control and need the long time until BLDCM reaches at the steady state. In order to improve the performance, this paper present the PI speed controller using the LQR based on vector control and the rotor position detection methods at the space vector PWM inverter. The proposed methods are proved by the simulation and experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.840-847
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• 2009

This paper deals with an $H_{\infty}$ output feedback controller design for uncertain singularly perturbed T-S fuzzy systems. Integral quadratic constraints are used to describe various kinds of uncertainties of the plant. It is shown that the $H_{\infty}$ norm of the uncertain singularly perturbed fuzzy system is less than $\gamma$ for a sufficiently small $\varepsilon$ > 0 if the $H_{\infty}$ norms of both the slow and fast subsystem are less than $\gamma$. Using this fact, we develop a linear matrix inequality based design method which is independent of the singular perturbation parameter $\varepsilon$. A numerical example is provided to demonstrate the efficacy of the proposed design method.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1102-1103
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• 2007

This Paper presents a solution to control the Brushless DC Motor(BLDCM) in Digital Lightening Processor(DLP) using the Linear Quadratic Regulator(LQR). Generally, The speed of BLDCM in DLP is controlled by the lead angle control or the input voltage control using PAM(Pulse Amplitude Modulation) etc. These control methods have speed overshoot in speed control and need the long time until BLDCM reaches at the steady state. In order to improve the performance, this paper present the PI speed controller using the LQR based on vector control and the rotor position detection methods at the space vector PWM inverter. The proposed methods are proved by the experimental results

• Smart Structures and Systems
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• v.16 no.6
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• pp.1133-1145
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• 2015

A new neural network (NN) predictive controller (NNPC) algorithm has been developed and tested in the computer simulation of active control of a nonlinear structure. In the present method an NN is used as a predictor. This NN has been trained to predict the future response of the structure to determine the control forces. These control forces are calculated by minimizing the difference between the predicted and desired responses via a numerical minimization algorithm. Since the NNPC is very time consuming and not suitable for real-time control, it is then used to train an NN controller. To consider the effectiveness of the controller on probability of damage, fragility curves are generated. The approach is validated by using simulated response of a 3 story nonlinear benchmark building excited by several historical earthquake records. The simulation results are then compared with a linear quadratic Gaussian (LQG) active controller. The results indicate that the proposed algorithm is completely effective in relative displacement reduction.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.1
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• pp.32-37
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• 1998

This paper deals with the implementation of a robust multivariable controller using DSP board and the application to real systems. The LQG/LTR (Linear Quadratic Gaussian with Loop Transfer Recovery) controller proposed by Doyle et al.[1,2] is adopted to design the control system. A helicopter propeller setup is taken as the controlled system in the current paper, and the mathematical model is derived to design the multivariable controller. The performance of the controller is evaluated via simulations, and implementation and application to the MIMO system shows that the control performances are satisfactory and superior to those of the PID controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.6
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• pp.40-50
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• 2002

In this paper, we present a GA(Genetic Algorithm) approach to select weighting matrices of an optimal LQ(Linear Quadratic) controller for SVC(Static VAR Compensator). A SVC, one of the FACTS(Flexible AC Transmission System), constructed by a FC(Fixed Capacitor) and a TCR(Thyristor Controlled Reactor), was designed and implemented to improve the damping of a synchronous generator, as well as to control the system voltage Also, a design of LQ controller depends on choosing weighting matrices. The selection of weighting matrices which is not a trivial solution is usually carried out by trial and error. We proposed an efficient method using GA of finding weighting matrices for optimal control law. Thus, we proved the usefulness of proposed method to improve the stability of single machine-infinite bus with SVC system by eigenvalues analysis and simulation.