• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.729-731
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• 2004

This paper deals with the design of a low order $H_{\infty}$ controller by using an iterative linear matrix inequality (LMI) method. The low order $H_{\infty}$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the effectiveness of the proposed algorithm.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.3
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• pp.231-239
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• 2002

Experiments on the single phase cooling heat transfer and pressure drop with microfin tubes were performed using water as a test fluid. Experimental data were obtained in the range of Reynolds number 3000 ~40000 and Prandtl number 4-6. The data of microfin tubes presented the characteristics of rough surface tube in pressure drop and heat transfer Experimental data were compared with the heat transfer and friction factor correlations of smooth tubes. Heat transfer enhancements of microfin tubes were lower than pressure drop penalty factors. The helix angle is more significant parameter in both of the pressure drop and heat transfer than the relative roughness. The correlations of Nusselt number and friction factor were suggested for the tested microfin tubes. Maximum deviations between correlations and experimental data were within $\pm15$% for Nusselt number and $\pm10$% for friction factor.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.428-431
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• 1995

In this paper we propose an on-line tuning method by using genetic algorithm for robust minimax I-PD controller based on new criterion. The new criterion is the Integral of Squared Error (ISE) with a penalty of the derivative of manipulated variable. The work focuses on robust tuning of I-PD controller's parameters in the presence of plant parameter uncertainty. The result of several simulation studies are provided to illustrate the performance of this robust tunig method.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.6
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• pp.477-484
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• 2002

A numerical investigation of the performance of the plate heat exchanger with rectangular winglet is conducted to examine the combined effect of vortex generator and louver fins. Velocity and temperature fields and spanwise averaged Nu and friction factor are presented. Enhancement of heat transfer and flow loss penalty is evident. A Parametric study of three factors (Re, angle of attack and louver angle) with levels of 5 (Re= 300, 500, 700, 900, 1100), 4($\alpha=15^{\circ}, 30^{\circ}, 45^{\circ}, 90^{\circ},$), and 4($\beta=0^{\circ}, 15^{\circ}, 30^{\circ}, 45^{\circ}$), respectively, indicates the performance defined by the ratio of heat transfer enhancement to flow loss penalty shows monotonic behavior for each parameter alone but the interactions between parameters is found to be considerable effect on the performance of heat exchanger and should be considered in design. The effect of stamping is also examined.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.4
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• pp.279-283
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• 2005

This paper deals with the design of a low-order H/sub ∞/ controller by using an iterative linear matrix inequality (LMI) method. The low-order H/sub ∞/ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, the recently developed penalty function method is applied. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. Numerical experiments showed the effectiveness of the proposed algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.656-661
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• 2005

This paper is concerned with an iterative linear matrix inequality (LMI) approach to the design of a structurally constrained output feedback controller such as decentralized control. The structured synthesis is formulated as a novel rank-constrained LMI optimization problem, where the controller parameters are explicitly described so as to impose structural constraints on the parameter matrices. An iterative penalty method is applied to solve the rank-constrained LMI problem. Numerical experiments are performed to illustrate the effectiveness of the proposed method.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.7
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• pp.178-187
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• 1999

In order to identify a transfer function model with noise, penalty function method has been widely used. In this method, estimation process for possible model parameters from low to higher order proceeds the model identification process. In this study, based on linear estimation method, a new approach unifying the estimation and the identification of ARMAX model is proposed. For the parameter estimation of a transfer function model with noise, linear estimation method by noise separation is suggested instead of nonlinear estimation method. The feasibility of the proposed model identification and estimation method is verified through simulations, namely by applying the method to time series model. In the case of time series model with noise, the proposed method successfully identifies the transfer function model with noise without going through model parameter identification process in advance. A new algorithm effectively achieving model identification and parameter estimation in unified frame has been proposed. This approach is different from the conventional method used for identification of ARMAX model which needs separate parameter estimation and model identification processes. The consistency and the accuracy of the proposed method has been verified through simulations.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.5
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• pp.853-859
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• 2022

In this study, we analyzed the instantaneous trajectory generation capability and target arrival rate of a mobile robot by changing the parameter of the TEB (Timed Elastic Band) Local Planner among local planners that affect the instantaneous obstacle avoidance ability of the mobile robot using ROS (Robot Operating System) simulation and real experience. As a result, we can expect a decrease in the target arrival time of the mobile robot through a decrease in the parameter values of the TEB Local Planner's min_obstacle_dist, inflation_dist, and penalty_epsilon. However, if this parameter is reduced too much, the risk of obstacle collision of the moving robot is increases, so it is important to combine the appropriate values to construct the parameter.

• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.357-365
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• 2011

This paper investigates a penalized likelihood method for estimating the parameter of normal mixtures in multivariate settings with full covariance matrices. The proposed model estimates the number of components through the addition of a penalty term to the usual likelihood function and the construction of a penalized likelihood function. We prove the consistency of the estimator and present the simulation results on the multi-dimensional nor-mal mixtures up to the 8-dimension.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.56-60
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• 1992

This paper addresses the problem of designing a neural network based controller for a discrete-time nonlinear dynamical system. Using two multi-layered neural networks we first design an indirect controller the weights of which are updated by the informations obtained from system identification. The weight update is executed by parameter optimization method under Lagrangian formulation. For the nonlinear dynamical system, we define several cost functions and by computer simulations analyze the control performances of them and the effects of penalty-weighting values.