• Earthquakes and Structures
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• v.22 no.1
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• pp.53-64
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• 2022

This study proposes an intelligent semi-active isolation system combining a variable-stiffness control device and ground motion characteristic prediction. To determine the optimal control parameter in real-time, a genetic algorithm (GA)-fuzzy control law was developed in this study. Data on various types of ground motions were collected, and the ground motion characteristics were quantified to derive a near-fault (NF) characteristic ratio by employing an on-site earthquake early warning system. On the basis of the peak ground acceleration (PGA) and the derived NF ratio, a fuzzy inference system (FIS) was developed. The control parameters were optimized using a GA. To support continuity under near-fault and far-field ground motions, the optimal control parameter was linked with the predicted PGA and NF ratio through the FIS. The GA-fuzzy law was then compared with other control laws to verify its effectiveness. The results revealed that the GA-fuzzy control law could reliably predict different ground motion characteristics for real-time control because of the high sensitivity of its control parameter to the ground motion characteristics. Even under near-fault and far-field ground motions, the GA-fuzzy control law outperformed the FPEEA control law in terms of controlling the isolation layer displacement and the superstructure acceleration.

• Journal of applied mathematics & informatics
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• v.13 no.1_2
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• pp.247-259
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• 2003

Optimal control problem for the exploitaton of oil is investigated. The optimal control problem under consideration in this paper is governed by weak coupled parabolic PDEs and involves with pointwise state and control constraints. The properties of solution of the state equations and the continuous dependence of state functions on control functions are investigated in a suitable function space; existence of optimal solution of the optimal control problem is also proved.

• Journal of Power System Engineering
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• v.15 no.2
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• pp.69-77
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• 2011

In this paper, an optimal PID sliding mode controller is proposed for the position control of electro-hydrostatic actuator(ERA) systems with system uncertainties and saturation in the motor. An ERA prototype is developed and system modeling and parameter identification are executed. Then, optimal PID and optimal anti-windup PID controller are designed based on identified system model by using optimization toolbox in MA TLAB/Simulink and the performance of the two control systems are compared by experiment. It was found that the optimal anti-windup PID control system has better performance than the optimal anti-windup PID control system.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.436-439
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• 1992

A tubular reactor model represented by partial differential equations was studied as one of nonlinear distributed parameter optimal control problems. An optimal control theory in the form of maximum principles based on nonlinear integral equations was used to develop an algorithm to solve the problem.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.575-577
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• 1987

A new control method for DC motor position control with variable structure is presented. The proposed method uses the desired trajectory with optimal input satisfying the given performance requirement as the switching curve and is insensitive to parameter variation and disturbance. To show the validity of the proposed method, digital computer simulation is performed. And the result is compared with that of the optimal state feedback.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.348-350
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• 2006

In this paper, we design a new controller for an ultra-precision positioning system. In general, time optimal control enables to reach a target position faster than others. However it shows a weakness to chattering effect. In order to solve the problem, a new control algorithm based on sliding mode control is proposed. The suggested controller is composed of LQR control and sliding mode control. By performing some simulations, we prove that the proposed controller is more robust than time optimal control under the circumstance of parameter uncertainties and external disturbances.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.116-120
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• 1989

The optimal control problem of linear Lumped Parameter Systems (LPS) and Distributed Parameter Systems (DPS) is studied by employing the technique of Walsh functions (WF). By the using the elegant operational properties of WF, a direct computational algorithm for evaluating the optimal control and trajectory of LPS and DPS is developed. Without the need of solving the traditional matrix Riccati equation, the WF approach in shown very simple in form and convenient for use of a computer. The approximation is in the sense of least squares employing WF as the basis and the results are in the piecewise constant and discrete form.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.549-551
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• 1998

In this paper, we design the optimal satellite-tracking antenna $H_{\infty}$ control system using genetic algorithm(GA). To do this, we give gain and dynamics parameters to the weighting functions and apply GA with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H_{\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are simultaneously optimized in tile search domain guaranteeing the robust stability of closed-loop system. The effectiveness of this satellite-tracking antenna $H_{\infty}$ control system is verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.73-77
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• 1986

Optimal input design problem for linear regression model with constrained output variance has been considered. It is shown that the optimal input signal for the linear regression model can also be realized as an ARMA process. Monte-Carlo simulation results show that the optimal stochastic input leads to comparatively better estimation accuracy than white input signal.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.6
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• pp.1-7
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• 2005

This paper deals with the position control for a feed drive system in CNC milling machine. The study shows that reduction in tacking error does not necessarily increase contouring accuracy, and proposes that a proper control scheme is able to exhibit the optimal tracking and contouring accuracy. The proposed scheme is to fix the parameter of the contouring control, and to find the optimal value of the parameter of the tracking control, which is automatically tuned. The effectiveness of the proposed scheme is confirmed through simulations.