• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.431-441
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• 1991

A robust H$_{\infty}$ control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multi-parameter variations in the state-space formulation of H$_{\infty}$ control theory. An application of this robust H$_{\infty}$ control synthesis technique to the Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73% in one of the structured uncertainty directions. The performance and stability of this new robust H$_{\infty}$ controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.que.

• Proceedings of the KSME Conference
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• 2001.11a
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• pp.646-653
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• 2001

LQG/LTR Control Methology is recently used for the analysis of multi-variable control in frequency domain. Target filter loop is designed by the demanding requirements such as cross-over frequency, disturbance rejection in low frequency domain, zero steady-state error, identification of maximum and minimum singular values and sensor noise rejection in high frequency domain. Loop transfer recovery is accomplished by solving the cheap control and then simulation close to the target filter loop. In this study, LQG/LTR Control Methodology is applied to the seat suspension system. It is found that this technique is very effective to control the system and improve the ride quality of human body.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.828-833
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• 2003

Rigid plate elastically supported at the edges is modeled and the performance of the optimal vibration control under sinusoidal excitation is tested. The controller based on the linear quadratic regulator with output feedback is designed to control the multi-degree of freedom vibration. Relative weighting parameters are considered as design constraints to determine the limitation of maximum control force and state parameters. Control force calculated by proportional output feedback of the displacement and velocity is used to suppress the vibration induced by the sinusoidal external force. The active vibration control of vibrating plate by the LQR controller is examined through the numerical simulations that show the effectiveness of optimal control scheme on the three degrees of freedom structure.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.2
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• pp.94-101
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• 1996

The equations of motion for a basic industrial robotic system which has a rigid or a flexible arm are derived by Lagrange's equation, respectively. Especially, for the deflection of the flexible arm, the assumed mode method is employed. These equations are highly nonlinear equations with nonlinear coupling between the variables of motion. In order to design the control law for the rigid-arm robot, Hunt-Su's nonlinear transformation method and Marino's feedback equivalence condition are used with linear quadratic regulator(LQR) theory. The control law for the rigid-arm robot is employed to input the desired path and to provide the required nonlinear transformations for the flexible-arm robot to follow. By using the implicit Euler method to solve the nonlinear equations, the comparison of the motions between the flexible and the rigid robots and the effect of flexibility are examined.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.8 s.173
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• pp.34-41
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• 2005

Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.7
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• pp.29-38
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• 1997

A closed-loop system modeling of an active/semiactive suspension system has been accomplished through an artificial neural network. A 7DOF full model as a system's equation of motion has been derived and an output feedback linear quadratic regulator has been designed for control purpose. A training set of a sample data has been obtained through a computer simulation. A 7DOF full model with LQR controller simulated under several road conditions such as sinusoidal bumps and rectangular bumps. A general multilayer perceptron neural network is used for dynamic modeling and target outputs are fedback to the a layer. A backpropagation method is used as a training algorithm. Model validation of new dataset have been shown through computer simulations.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.09a
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• pp.373-380
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• 2001

In this research, a controller design method based on optimization is proposed that can satisfy constraints on maximum responses of building structures subject to ground excitation modeled by partially stationary stochastic process. The class of controllers to be optimized is restricted to LQR. Weighting matrix on controlled outputs is used as design variable. Objective function constraint functions and their gradients are computed parameterizing control gain with Riccati matrix. Full state feedback controllers designed by Proposed optimization method satisfy various design objectives and their necessary maximum control forces are computed fur the production of actuator. Probabilities of maximum responses match statistical data from simulation results well.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.1
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• pp.12-20
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• 2002

To control the noise of an enclosed sound field, we built a state space model using the acoustic modal parameter description. Using the state space model, we can investigate the controllability and observability, and find an appropriate position of control speaker and microphone to control sound field of the enclosed space. We implemented LQR(linear quadratic regulator) controller and reduced order observer to reduce the first acoustic mode. Experiments showed satisfactory results of 4∼10 dB reduction of magnitude of the first acoustic mode, and support the feasibility of the proposed scheme to lightly damped acoustic field.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.04a
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• pp.713-719
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• 2012

This paper is concerned with the dynamic modeling for the hardware-in-the-loop simulation of lateral vibrations of a railway vehicle. The resulting dynamic model is a nine degree-of-freedom model which can describe the lateral, roll and yaw motions of the car body and two bogies. It is assumed that the external disturbances come from wheel motions. In order to test the efficacy of the model, the linear quadratic regulator and the sky-hook control algorithm were designed and applied to the model. The simulation results show that both control algorithms are effective in suppressing the vibrations of railway vehicles.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.634-641
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• 2012

This paper is concerned with the dynamic modeling for the hardware-in-the-loop simulation of lateral vibrations of a railway vehicle. The resulting dynamic model is a nine degree-of-freedom model which can describe the lateral, roll and yaw motions of the car body and two bogies. It is assumed that the external disturbances come from wheel motions. In order to test the efficacy of the model, the linear quadratic regulator and the sky-hook control algorithm were designed and applied to the model. The simulation results show that both control algorithms are effective in suppressing the vibrations of railway vehicles.