• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1766-1767
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• 2011

본 논문에서는 기존의 proportional-integral-derivative (PID) 제어기의 이득조정과정에서 linear quadratic regulator(LQR)을 이용하여 이득조정을 하는 방법을 제안한다. 제안된 제어기의 이득은 LQR의 수식으로 표현되어지며 Matlab/simulink을 이용한 모의실험을 통해 위치프로파일에 대한 위치추종오차의 성능이 평가되어진다.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.5
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• pp.99-107
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• 2003

In a winding process, important control specifications include regulation of web tension and velocity. In this research, an adaptive controller has been developed for controlling web tension and velocity in winding processes. For the controller design, the linear quadratic regulator theory has been adopted and a gain-scheduling scheme has been incorporated. A prototype winding system has been constructed, and the controller has been implemented in a real-time PC-based environment. The performance of the closed loop system has been evaluated via simulation and experiments, and it was observed that both the web tension and velocity could be regulated within a small tolerance.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.11
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• pp.1809-1818
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• 1997

Mathematical models of industrial robots or manipulators are highly nonlinear equations with nonlinear coupling between the variables of motion. As the working speed has been fast, the effects of nonlinear terms have become serious. So the control algorithm based on approximately linearized equation looses the efficiency. In order to design the control law for the nonlinear models, Hunt-Su's nonlinear transformation method and Marino's feedback equivalence condition are used with linear quadratic regulator(LQR) theory in this study. Nonlinear terms of the system are eliminated and coupled terms are decoupled by this feedback law. This method is applied to a 3-D.O.F. vertical articulated manipulator by both experiments and simulations and compared with PID control which is widely used in the industry.

• Journal of the Korean Society of Industry Convergence
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• v.2 no.1
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• pp.61-67
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• 1999

An active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. And We designed controller by fuzzy learning method, and then compare fuzzy learning method with LQR. The result of simulations shows that the crane is controlled better than LQR for a very large swing angle of 1 radian within nearly one cycle.

• International Journal of Aeronautical and Space Sciences
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• v.7 no.2
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• pp.121-127
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• 2006

An analysis procedure for the combined problem of control algorithm and aeroelastic system which is based on the computational fluid dynamics(CFD) technique has been developed. The aerodynamic forces in the transonic region are calculated from the transonic small disturbance(TSD) theory. An linear quadratic regulator(LQR) controller is designed to suppress the transonic flutter. The optimal control gain is estimated by solving the discrete-time Riccati equation. The system identification technique rebuilds the CFD-based aeroelstic system in order to form an adequate system matrix which involved in the discrete-time Riccati equation. Finally the controller, that is constructed on the basis of system identification technique, is used to suppress the flutter phenomenon of the airfoil with attached store. This approach, that is, the CFD-based aeroservoelasticity design, can be utilized for the development of effective flutter controller design in the transonic region.

• Structural Engineering and Mechanics
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• v.17 no.3_4
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• pp.593-609
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• 2004

Peak response is a more suitable index than mean response in the light of structural safety. In this study, a controller optimization method is proposed to restrict peak responses of building structures subject to earthquake excitations, which are modeled as partially stationary stochastic process. The constraints are given with specified failure probabilities of peak responses. LQR is chosen to assure stability in numerical process of optimization. Optimization problem is formulated with weightings on controlled outputs as design variables and gradients of objective and constraint functions are derived. Full state feedback controllers designed by the proposed method satisfy various design objectives and output feedback controllers using LQG also yield similar results without significant performance deterioration.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.1775-1776
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• 2006

This paper deals with the problem of friction measurement of an inverted pendulum system using the regression analysis and proposes a solution. The approach taken in this study is getting the friction from a regression relational expression between the motor voltage and the cart velocity of an inverted pendulum system. The result to compensate LQR (linear Quadratic Regulator) controller with the friction which is measured in system, improved the performance of the system. Above all, the study has found that the proposed compensation of the friction reduces the oscillation of the cart position. In conclusion, the proposed method is useful when parameters in the given system model are not known.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.871-875
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• 1996

The Output feedback linear quadratic regulator control is applied to the design of active suspension system using 7 DOF full car model. The performance index reflects the vehicle vertical movement, pitch and roll motion, and minimization of suspension stroke displacements in the rattle space. The elements of gain matrix are approximately decoupled so that each suspension requires only local information to generate the control force. The simulation results indicates that the output feedback LQ controller is more effective than purely passive or full state feedback active LQ controllers in following the road profile at the low frequency range and suppressing the road disturbance at the high frequency ranges.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.1-9
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• 2006

This paper presents the modeling and multivariable feedback control of a novel high-precision multi-dimensional positioning stage. This integrated 6-degree-of-freedom. (DOF) motion stage is levitated by three aerostatic bearings and actuated by 3 three-phase synchronous permanent-magnet planar motors (SPMPMs). It can generate all 6-DOF motions with only a single moving part. With the DQ decomposition theory, this positioning stage is modeled as a multi-input multi-output (MIMO) electromechanical system with six inputs (currents) and six outputs (displacements). To achieve high-precision positioning capability, discrete-time integrator-augmented linear-quadratic-regulator (LQR) and reduced-order linearquadratic-Gaussian (LQG) control methodologies are applied. Digital multivariable controllers are designed and implemented on the positioning system, and experimental results are also presented in this paper to demonstrate the stage's dynamic performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.71-76
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• 2008

This paper is concerned with the active vibration control of elevator by means of the active roller guide. To this end, a dynamic model for the horizontal vibration of the elevator consisting of a supporting frame, cage and active roller guides was derived using the energy method. Free vibration analysis was then carried out based on the equations of motion. Active vibration controller was designed based on the equations of motion using the LQR theory and applied to the numerical model. Rail irregularity and wind pressure variation were considered as external disturbance in the numerical simulations. The numerical results show that the active vibration control of elevator is possible.