• Journal of Institute of Control, Robotics and Systems
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• v.6 no.6
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• pp.500-505
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• 2000

This paper deals with wafer temperature uniformity control essential in rapid thermal processing (RTP). One of the important control objectives of RTP is to keep the temperature over the wafer surface as uniformly as possible. For this, a discrete time state equation around the operating point is first identified by using the subspace fitting method, and a multivariable LQG(Linear Quadratic Gaussian) controller is designed based on the identified model. Simulation and experimental results show improvement in temperature uniformity over the conventional PID method.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.121-124
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• 1989

In this thesis, a decomposed LQG/LTR controller is designed for an undersea vehicle. The modellig error which results from decomposition of the original model is considered to the design specification for maintaining the robust stability. The LQG/LTR controller designed with new specification is simulated.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.395-400
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• 1991

In spinning satellite, a gyrotorquer generates a control torquer along two orthogonal axes normal to the spin axis of the vehicle. Matrix Fraction Description(MFD) are used to obtain minimal realization of the transfer matrix relating the attitude angles and the rate of rotation of the gimbals of gyrotorquer. In this paper, the Linear Quadratic Gaussian with Loop Transfer Recovery and H.meihodologies are used to design controller for spinning satellite.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.218-223
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• 1997

The technique used is the active structural acoutrol (ASAC)approach which involves controlling the acoustic response of a panel-cavity covpled system by applying oscillating force inputs in the form of prezoelectric actuators directly to the flexible panel. The linear quadratic Gaussian control scheme is used for attenuating nosie inside the rectangular enclosure causing by flexible wall vibration. Results indicated the application of control inputs to the radiating wall resukted in considerable noise reductions inside the cavity. Auso,the possibility of application to the more complicated fluid-structure coupled system is verified.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.9
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• pp.920-928
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• 1991

This paper proposes a design procedure based on the LQG/LTR (Linear Quadratic Gaussian/ Loop Transfer Recovery) method for a launch vehicle. Continuous-discrete type LQG/LTR compensators are designed using the e-transformation to overcome numerical problems occurring in the process of discretization. The e-LQG/LTR compensator using the e-transformation is compared width the z-LQG/LTR compensator using the z-transformation. The performance of the overall system controlled by the compensator is evaluated via simulations, which show that the discretization error problem is resolved and the control performances are satisfactory in the proposed compensator.

• Journal of Mechanical Science and Technology
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• v.16 no.12
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• pp.1561-1575
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• 2002

A reduced-order linear feedback controller, which is used to control the linear disturbance in two-dimensional plane Poiseuille flow, is applied to a boundary layer flow for stability control. Using model reduction and linear-quadratic-Gaussian/loop-transfer-recovery control synthesis, a distributed controller is designed from the linearized two-dimensional Navier-Stokes equations. This reduced-order controller, requiring only the wall-shear information, is shown to effectively suppress the linear disturbance in boundary layer flow under the uncertainty of Reynolds number. The controller also suppresses the nonlinear disturbance in the boundary layer flow, which would lead to unstable flow regime without control. The flow is relaminarized in the long run. Other effects of the controller on the flow are also discussed.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.337-339
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• 2004

In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs). Proceeding the layer, this model creates the optimal network architecture through the selection and the elimination of nodes by itself. So, there is characteristic of flexibility. We use a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. GAs is applied to improve the performance with optimal input variables and number of input variables and order. To evaluate the performance of the GAs-based FPNNs, the models are experimented with the use of Medical Imaging System(MIS) data.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2946-2948
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• 2000

In this paper, we proposed the Fuzzy Polynomial Neural Networks(FPNN) model with fuzzy activation node. The proposed FPNN structure is generated from the mutual combination of PNN(Polynomial Neural Networks) structure and fuzzy inference system. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. The structure of FPNN is not fixed like in conventional Neural Networks and can be generated. The design procedure to obtain an optimal model structure utilizing FPNN algorithm is shown in each stage. Gas furnace time series data used to evaluate the performance of our proposed model.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.152-155
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• 1994

The presence of joint elasticity or the arm flexibility causes low damped oscillatory position error along a desired trajectory. We utilize a stochastic model for describing the fast dynamics and the approximation error. A second order shaping filter is synthesized such that its spectrum matches that of the fast dynamics. Augmenting the state vector of slow part with that of shaping filter, we obtain a nonlinear dynamics to which a Gaussian white noise is injected. This modeling approach leads us to the design of an extended Kalman filter(KEF) and a linear quadratic Gaussian(LQG) control scheme. We present the simulation results of this control method. The simulation results show us that our Kalman filtering approach is one of prospective methods in controlling the flexible arms.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.43-56
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• 2011

An integrated system composed of guidance, navigation and control (GNC) system for autonomous proximity operations and the docking of two spacecraft was developed. The position maneuvers were determined through the integration of the state-dependent Riccati equation formulated from nonlinear relative motion dynamics and relative navigation using rendezvous laser vision (Lidar) and a vision sensor system. In the vision sensor system, a switch between sensors was made along the approach phase in order to provide continuously effective navigation. As an extension of the rendezvous laser vision system, an automated terminal guidance scheme based on the Clohessy-Wiltshire state transition matrix was used to formulate a "V-bar hopping approach" reference trajectory. A proximity operations strategy was then adapted from the approach strategy used with the automated transfer vehicle. The attitude maneuvers, determined from a linear quadratic Gaussian-type control including quaternion based attitude estimation using star trackers or a vision sensor system, provided precise attitude control and robustness under uncertainties in the moments of inertia and external disturbances. These functions were then integrated into an autonomous GNC system that can perform proximity operations and meet all conditions for successful docking. A six-degree of freedom simulation was used to demonstrate the effectiveness of the integrated system.