• Journal of the Chungcheong Mathematical Society
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• v.17 no.2
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• pp.169-190
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• 2004

Let r, s be nonzero real numbers. Let X, Y be vector spaces. It is shown that if a mapping f : $X{\rightarrow}Y$ satisfies f(0) = 0, and $$sf(\frac{x+y{\pm}z}{r})+f(x)+f(y){\pm}f(z)=sf(\frac{x+y}{r})+sf(\frac{y{\pm}z}{r})+sf(\frac{x{\pm}z}{r})$$, or $$sf(\frac{x+y{\pm}y}{r})+f(x)+f(y){\pm}f(z)=f(x+y)+f(y{\pm}z)+f(x{\pm}z)$$ for all x, y, $z{\in}X$, then there exist an additive mapping A : $X{\rightarrow}Y$ and a quadratic mapping Q : $X{\rightarrow}Y$ such that f(x) = A(x) + Q(x) for all $x{\in}X$. Furthermore, we prove the Cauchy-Rassias stability of the functional equations as given above.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.16 no.3
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• pp.293-302
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• 2004

In this study the optimization of plate-fin type heat sink for the thermal stability is peformed numerically. The optimum design variables are obtained when the temperature rise and the pressure drop are minimized simultaneously. The flow and thermal fields are predicted using the finite volume method and the optimization is carried out by using the sequential quadratic programming (SQP) method which is widely used in the constrained non-linear optimization problem. The results show that when the temperature rise is less than 34.6K, the optimal design variables are as follows; B$_1$=2.468mm, B$_2$=1.365mm, and t=10.962mm. The Pareto optimal solutions are also presented for the pressure drop and the temperature rise.

• Earthquakes and Structures
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• v.21 no.6
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• pp.577-585
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• 2021

In this research, a neural network (NN) method was developed, which combines H-infinity and fuzzy control for the purpose of stabilization and stability analysis of nonlinear systems. The H-infinity criterion is derived from the Lyapunov fuzzy method, and it is defined as a fuzzy combination of quadratic Lyapunov functions. Based on the stability criterion, the nonlinear system is guaranteed to be stable, so it is transformed to be a linear matrix inequality (LMI) problem. Since the demo active vibration control system to the tuning of the algorithm sequence developed a controller in a manner, it could effectively improve the control performance, by reducing the wind's excitation configuration in response to increase in the cost efficiency, and the control actuator.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.51-57
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• 2022

The problem of optimal stochastic GA control of the system with uncertain parameters and unsure noise covariates is studied. First, without knowing the explicit form of the dynamic system, the open-loop determinism problem with path optimization is solved. Next, Gaussian linear quadratic controllers (LQG) are designed for linear systems that depend on the nominal path. A robust genetic neural network (NN) fuzzy controller is synthesized, which consists of a Kalman filter and an optimal controller to assure the asymptotic stability of the discrete control system. A simulation is performed to prove the suitability and performance of the recommended algorithm. The results indicated that the recommended method is a feasible method to improve the performance of active tuned mass damper (ATMD) shear buildings under random earthquake disturbances.

• Steel and Composite Structures
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• v.42 no.5
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• pp.711-722
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• 2022

In this paper, hyperbolic shear deformation plate theory is developed for thermal buckling of functionally graded plates with porosity by dividing transverse displacement into bending and shear parts. The present theory is variationally consistent, and accounts for a quadratic variation of the transverse shearstrains across the thickness and satisfies the zero traction boundary conditions on the top and bottom surfaces of the plate without using shear correction factors. Three different patterns of porosity distributions (including even and uneven distribution patterns, and the logarithmic-uneven pattern) are considered. The logarithmic-uneven porosities for first time is mentioned. Equilibrium and stability equations are derived based on the present theory. The non-linear governing equations are solved for plates subjected to simply supported boundary conditions. The thermal loads are assumed to be uniform, linear and non-linear distribution through-the-thickness. A comprehensive parametric study is carried out to assess the effects of volume fraction index, porosity fraction index, aspect ratio and side-to-thickness ratio on the buckling temperature difference of imperfect FG plates.

• The Transactions of the Korean Institute of Power Electronics
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• v.16 no.2
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• pp.162-172
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• 2011

This paper proposes embedded System of two wheeled inverted pendulum robot designed by model based design method, using MATLAB/SIMULINK and LEGO NXT Mindstorms. At first, stability and performance of controller is verified through modeling and simulation. After that direct conversion from simulation model to C code is carried and effectiveness of controller is experimentally verified. Two wheeled inverted pendulum robot has basic function about autonomous balancing control using principle of inverted pedulum and it is also possible to arrive at destination. In this paper, state feedback controller designed by quadratic optimal control method is used. And quadratic optimal control uses state feedback control gain K to minimize performance index function J. Because it is easy to find gain, this control method can be used in the controller of two wheeled inverted pendulum robot. This proposed robot system is experimentally verified with following performances - balancing control, disturbance rejection, remote control, line following and obstacle avoidance.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.37-45
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• 2016

Control chart is representative tools of statistical process control (SPC). It is a graph that plotting the characteristic values from the process. It has two steps (or Phase). First step is a procedure for finding a process parameters. It is called Phase I. This step is to find the process parameters by using data obtained from in-controlled process. It is a step that the standard value was not determined. Another step is monitoring process by already known process parameters from Phase I. It is called Phase II. These control chart is the process quality characteristic value for management, which is plotted dot whether the existence within the control limit or not. But, this is not given information about the economic loss that occurs when a product characteristic value does not match the target value. In order to meet the customer needs, company not only consider stability of the process variation but also produce the product that is meet the target value. Taguchi's quadratic loss function is include information about economic loss that occurred by the mismatch the target value. However, Taguchi's quadratic loss function is very simple quadratic curve. It is difficult to realistically reflect the increased amount of loss that due to a deviation from the target value. Also, it can be well explained by only on condition that the normal process. Spiring proposed an alternative loss function that called reflected normal loss function (RNLF). In this paper, we design a new control chart for overcome these disadvantage by using the Spiring's RNLF. And we demonstrate effectiveness of new control chart by comparing its average run length (ARL) with ${\bar{x}}-R$ control chart and expected loss control chart (ELCC).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.749-757
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• 2021

In transportation missions using quadrotor, the payload may change the model parameters, such as mass, moment of inertia, and center of gravity. Moreover, if position of the payload is constantly changing during flight, the effect can adversely affect the control performances. To handle this issue, we suggest Model Reference Adaptive Control based on Linear Quadratic Regulator(LQR+MRAC) to compensate the uncertainty caused by payload. Firstly, the mathematical modeling with the fixed payload is derived. Second, Linear Quadratic Regulator (LQR) is used to design the reference model and baseline controller. Also, through the Stability method, Adaptive law is derived to estimate the model parameters. To verify the performance of proposed control scheme, we compared LQR and LQR+MRAC in situations where uncertainties exist. And, when the disturbance exist, the classic MRAC and proposed controller is compared to analyze the transient response and robustness.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.365-370
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• 2000

A sliding mode fuzzy control (SMFC) algorithm is applied to design a controller for a benchmark problem on a wind- excited building. The structure is a 76-story concrete office tower with a height of 306 meters, hence the wind resistance characteristics are very important for the serviceability as well as the safety. A control system with an active tuned mass damper is assumed to be installed on the top floor. Since the structural acceleration is measured only at ,limited number of locations without measurement of the wind force, the structure of the conventional continuous sliding mode control may have the feed-back loop only. So, an adaptive least mean squares (LMS) filter is employed in the SMFC algorithm to generate a fictitious feed-forward loop. The adaptive LMS filter is designed based on the information of the stochastic characteristics of the wind velocity along the structure. A numerical study is carried out. and the performance of the present SMFC with the ,adaptive LMS filter is investigated in comparison with those of' other control, of algorithms such as linear quadratic Gaussian control, frequency domain optimal control, quadratic stability control, continuous sliding mode control, and H/sub ∞///sub μ/, control, which were reported by other researchers. The effectiveness of the adaptive LMS filter is also examined. The results indicate that the present algorithm is very efficient .

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.190.1-190.1
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• 2015

Graphite has excellent mechanical and physical properties. It is known to advanced materials and is used to materials for molds, thermal treatment of furnace, sinter of diamond and cemented carbide tool etc. SiC materials are coated on the surface and holes of graphite to protect particles emitted from porous graphite with 5%~20% porosity and make graphite hard surface. SiC materials have high durability and thermal stability. Thermal CVD method is widely used to manufacture SiC thin films but high cost of machine investment and production are required. SiC thin films manufactured by Si reaction liquid and vapore with carbon are effective because of low cost of machine and production. SiC thin films made by vapor silicon infiltration into porous graphite can be obtained for shorter time than liquid silicon. Si materials are evaporated to the graphite surface in about $10^{-2}$ torr and high temperature. Si materials are melted in $1410^{\circ}C$. Si vapor is infiltrated into the surface hole of porous graphite and $Si_xC_y$ compound is made. $Si_x$ component is proportional to the Si vapor concentration. Si diffusion coefficient is estimated from quadratic equation obtained by Fick's second law. The steady stae is assumed. Si concentration variation for the depth from graphite surface is fitted to quadratic equation. Diffusion coefficient of Si vapor is estimated at about $10^{-8}cm^2s^{-1}$.