• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2212-2214
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• 2004

Robust stable analysis with the system bounded parameteric variation is very important among the various control theory. This study is to investigate the robust stable conditions using the quadratic form Lyapunov function in which the coefficient matrix is affined linear system. The quadratic stability using the quadratic form Lyapunov function is not investigated yet. The Lyapunov unction is robust stable not to be dependent by the variable parameters, which means that the Lyapunov function is conservative. We suggest the robust stable conditions in the Lyapunov function in which the variable parameters are dependent in order to reduce the conservativeness of quadratic stability.

• Journal of Advanced Navigation Technology
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• v.21 no.5
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• pp.450-458
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• 2017

This paper presents dynamic modelling and simulation study on attitude/altitude control of an insect-mimicking flapping micro aerial vehicle during hovering. Mathematical modelling consists of three parts: simplified flapping kinematics, flapping-wing aerodynamics, and six degree of freedom dynamics. Attitude stabilization is accomplished through linear quadratic regulator based on the linearized model of the time-varying nonlinear system, and altitude control is designed in the outer loop using PID control. The performance of the proposed controller is verified through numerical simulation where attitude stabilization and altitude control is done for hovering. In addition, it is confirmed that the attitude channel by periodic control is marginally stable against periodic pitching moment caused by flapping.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.5-75
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• 2001

In this paper, we study design of a ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between stands plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. A Looper servo controller is designed by ILQ control theory which is an inverse problem of LQ(Linear Quadratic optimal control) control. The mathematical model for looper system is obtained by Taylor´s linearization of nonlinear differential equations. Then we designed linear controller for linearization model by using the ILQ control algorithm. Thereafter this controller is applied to the nonlinear model for model identification. As a result, we show the controller´s robustness for the model error, external disturbance and sensor noise.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.219-224
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• 1992

This paper deals with the linear quadratic optimal regulator problem for descriptor systems without performing a preliminary transformation for a descriptor system. We derive a generalized Riccati differential equation (GRDE) based on the two-point boundary value problem for a Hamiltonian equation. We then obtain an optimal feedback control and the optimal cost in terms of the solution of GRE. A simple example is included.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.18 no.3
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• pp.269-277
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• 2014

A numerical scheme is proposed to control the BBMB (Benjamin-Bona-Mahony-Burgers) equation, and the scheme consists of three steps. Firstly, BBMB equation is converted to a finite set of nonlinear ordinary differential equations by the quadratic B-spline finite element method in spatial. Secondly, the controller is designed based on the linear quadratic regulator (LQR) theory; Finally, the system of the closed loop compensator obtained on the basis of the previous two steps is solved by the backward Euler method. The controlled numerical solutions are obtained for various values of parameters and different initial conditions. Numerical simulations show that the scheme is efficient and feasible.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1382-1386
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• 2003

In this paper, we propose a controller for the position of a cart and the angle of a pendulum. To achieve both purposes simultaneously, we divide the system into the dominant subsystem and the dominated one after partial feedback linearization. The proposed controller is composed of a nonlinear controller stabilizing the dominant subsystem and a linear quadratic controller. Using the proposed controller, the controllable region is increased by the nonlinear control part and the control input minimized by the linear control part (LQR).

• Coupled systems mechanics
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• v.13 no.1
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• pp.73-93
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• 2024

In this work, we propose combining an advanced optimal control algorithm with a geometrically exact beam model. For simplicity, the 2D Reissner beam model is chosen to represent large displacements and rotations. The difficulty pertains to the nonlinear nature of beam kinematics affecting the tangent stiffness matrix, making it non-constant, which compromises direct use of optimal control methods for linear problems. Thus, we seek to accommodate a time varying control using linear-quadratic regulator (LQR) algorithm with the proposed geometrically nonlinear beam model. We provide a detailed theoretical formulation and its numerical implementation in a variational format form. Several illustrative numerical examples are provided to confirm an excellent performance of the proposed methodology.

• Animal Bioscience
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• v.36 no.3
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• pp.498-505
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• 2023

Objective: This study was conducted to determine the optimal dose of novel iron amino acid complexes (Fe-Lys-Glu) by measuring laying performance, egg quality, egg iron (Fe) concentrations, and blood biochemical parameters in laying hens. Methods: A total of 1,260 18-week-old healthy Beijing White laying hens were randomly divided into 7 groups with 12 replicates of 15 birds each. After a 2-wk acclimation to the basal diet, hens were fed diets supplemented with 0 (negative control, the analyzed innate iron content was 75.06 mg/kg), 15, 30, 45, 60, and 75 mg Fe/kg as Fe-Lys-Glu or 45 mg Fe/kg from FeSO₄ (positive control) for 24 wk. Results: Results showed that compared with the negative and positive control groups, dietary supplementation with 30 to 75 mg Fe/kg from Fe-Lys-Glu significantly (linear and quadratic, p<0.05) increased the laying rate (LR) and average daily egg weight (ADEW); hens administered 45 to 75 mg Fe/kg as Fe-Lys-Glu showed a remarkable (linear, p<0.05) decrease in feed conversion ratio. There were no significant differences among all groups in egg quality. The iron concentrations in egg yolk and serum were elevated by increasing Fe-Lys-Glu levels, and the highest iron content was found in 75 mg Fe/kg group. In addition, hens fed 45 mg Fe/kg from Fe-Lys-Glu had (linear and quadratic, p<0.05) higher yolk Fe contents than that with the same dosage of FeSO₄ supplementation. The red blood cell (RBC) count and hemoglobin content (linear and quadratic, p<0.05) increased obviously in the groups fed with 30 to 75 mg Fe/kg as Fe-Lys-Glu in comparison with the control group. Fe-Lys-Glu supplementation also (linear and quadratic, p<0.05) enhanced the activity of copper/zinc-superoxide dismutase (Cu/Zn-SOD) in serum, as a result, the serum malonaldehyde content (linear and quadratic, p<0.05) decreased in hens received 60 to 75 mg Fe/kg as Fe-Lys-Glu. Conclusion: Supplementation Fe-Lys-Glu in laying hens could substitute for FeSO₄ and the optimal additive levels of Fe-Lys-Glu are 45 mg Fe/kg in layers diets based on the quadratic regression analysis of LR, ADEW, RBC, and Cu/Zn-SOD.

• Korean Journal of Mathematics
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• v.25 no.1
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• pp.45-60
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• 2017

This paper focuses on estimation of an non-integral quadratic function (NIQF) and integral quadratic function (IQF) of a random signal in dynamic system described by a linear stochastic differential equation. The quadratic form of an unobservable signal indicates useful information of a signal for control. The optimal (in mean square sense) and suboptimal estimates of NIQF and IQF represent a function of the Kalman estimate and its error covariance. The proposed estimation algorithms have a closed-form estimation procedure. The obtained estimates are studied in detail, including derivation of the exact formulas and differential equations for mean square errors. The results we demonstrate on practical example of a power of signal, and comparison analysis between optimal and suboptimal estimators is presented.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.56.5-56
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• 2002

This paper studies on the feedback linearization of the looper system for hot strip mills, where the looper system plays an important role in regulating the strip tension. Firstly, nonlinear dynamic equations of the looper system are simply introduced. Secondly, using the static feedback linearization algorithm, a linear model of the looper system is obtained, of which usefulness is validated from comparison between the linear model and the nonlinear model, and design of LQI(Linear Ouadratic Integral optimal control) and ILQ (Inverse Linear Quadratic optimal control) looper control systems. In result, it is shown that the linear looper model by the feedback linearization well describes nonlin...