• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.71-81
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• 2001

This paper analyzes the effectiveness of minimizing vibration and sound transmission on/through a thin rectangular plate by both feedback control and hybrid control which combines adaptive feedforward control with a feedback loop. An experimental system identification technique using the matrix-fractional curve-fitting of the frequency response data is introduced for complex shaped structures. This identification technique reduces the model order o the MIMO(Multi-Input Multi-Output) system which simplifies the practical implementation. The adaptive feedforward control uses a Multiple filtered-x LMS(Least Mean Square) algorithm and the feedback control uses a multivariable digital LQG(Linear Quadratic Gaussian) algorithm. Experimental results show that an effective reduction of sound transmission is achieved by the hybrid control scheme when both vibration and noise measurement signals are incorporated in the controller.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.339-347
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• 2001

A probabilistic optimum design method of the base isolation system consisting of linear spring, viscous damper and frictional element is presented. For the probabilistic approach, the base excitation is assumed to be a stationary Gaussian filtered random process. For optimum design, the objective function and constraints are derived based on the stochastic responses of the system. As a numerical example, the optimum design problem of a three-story base isolated shear type structure is formulated and solved by the sequential quadratic programming method. As a result, the effects of variation of design variables such as parameters of the base isolation system and the mass of base on the objective function and constraints are investigated and the optimum parameters of the base isolation system under study are derived.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2005.03a
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• pp.388-395
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• 2005

This paper presents cost-effectiveness evaluation of semi-active control system for cable-stayed bridge under earthquake excitation. Bi-state control method with Linear Quadratic Gaussian(LQG) optimal controller is used for generic semi-active dampers. Cost-effectiveness of the structural control system is investigated by using the life-cycle cost(LCC) concept. The evaluation results show that the efficiency of semi-active control system is increased when the damage cost due to the failure of bridge system or the bridge importance is enlarged. It was also found that the damper cost had little influence on the cost-effectiveness of semi-active control system if it was relatively small to the initial construction cost.

• Proceedings of the KSR Conference
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• 2006.11a
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• pp.145-159
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• 2006

This paper describes the development of a clustering based fuzzy controller of an electromagnetic suspension vehicle using gain scheduling method and Kalman filter for a simplified single magnet system. Electromagnetic suspension vehicle systems are highly nonlinear and essentially unstable systems For achieving the levitation control of the DC electromagnetic suspension system, we considered a fuzzy system modeling method based on clustering algorithm which a set of input/output data is collected from the well defined Linear Quadratic Gaussian(LQG) controller. Simulation results show that the proposed clustering based fuzzy controller methodology robustly yields uniform performance with adequate gap response over the mass variation range.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.369-373
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• 1992

Force control of a planar two-link structurally flexible robotic manipulator is considered in this study. The dynamic model is obtained by using the extended Hamilton's principle and the Galerkin criterion. A method is pressented toobtain the linearized equations of motion in Cartesian space for use in designing the control system. The approachto solving the control problem is to use feedforward and feedback control torques. The feedforward torques maneuver the flexible manipulatro along a nominal trajectory and the feedback torques minimize any deviations from the nominal trajectory. The linear quadratic Gaussian/loop transfer recovery (LQG/LTR) design methodology is explotied to design a robust feedback control system that can handle modeling errors and sensor noise, and operates on Cartesian space trajectory errors. The Lqg/LTR compenstaor together with a feedforward ollp is used to control the flexible manipulator. Simulated results are presented for a numerical example.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.15-15
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• 2000

In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.356-360
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• 1990

This paper is an application of Modern control Theory to the control of a current-source inverter (CSI) fed Induction Motor Drive System. A Linear Quadratic-Gaussian (LQG) scheme is developed, in which the Kalman Filter is tuned for high robustness by a method due to Doyle and Stein(8). The design is carried out for a sample system and the robustness by analysis and computer simulation.

• 한국가시화정보학회:학술대회논문집
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• 2004.12a
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• pp.47-55
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• 2004

Several interpolations for image deformation in PIV were evaluated. The tested interpolation methods are linear, quadratic, truncated sinc, windowed sinc, cubic, Lagrange, Gaussian $2^{nd}\;and\;6^{th}$ interpolators. Bias errors and random errors were evaluated in the range of $0\~3.0$ pixel uniform displacement using synthetic images. We also measured the time cost of each interpolator with respect to kernel size. The cubic interpolator with $6\times6$ kernel showed the best results in terms of the performance and time cost.