• Journal of the Korean Society of Industry Convergence
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• v.2 no.1
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• pp.61-67
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• 1999

An active control for the swing of crane systems is very important for increasing the productivity. This article introduces the control for the position and the swing of a crane using the fuzzy learning method. Because the crane is a multi-variable system, learning is done to control both position and swing of the crane. Also the fuzzy control rules are separately acquired with the loading and unloading situation of the crane for more accurate control. And We designed controller by fuzzy learning method, and then compare fuzzy learning method with LQR. The result of simulations shows that the crane is controlled better than LQR for a very large swing angle of 1 radian within nearly one cycle.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2240-2242
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• 2001

A rotary double inverted pendulum, the nonlinear system has a regulation problem. In this paper, we linearize the nonlinear system at the upright equilibrium position. The linearized system can be expressed in state space. To maintain the upright position, we design a feedback controller using LQR(Linear Quadratic Regulator) algorithm. Then we simulate the system with third-order Adams Bashforth Moulton Method. The simulated result shows that the applied algorithm is effective for the regulation problem.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.41.4-41
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• 2001

In this paper, we propose a LQR(Linear Quadratic Regulator) controller design for the active suspension using two-degree-of-freedom quarter-car model. We can improve the inherent suspension problem, the tradeoff between ride quality and suspension travel by selecting appropriate weights in the LQR-objective function. Because any definite rules for selecting weights do not exist, we replace the designer´s trial and error with the optimization-algorithm, ES(Evolution Strategy). Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle´s state variables.

• 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).

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.3
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• pp.209-217
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• 2001

In this paper, we propose a linear quadratic regulator(LQR) controller design for the active suspension using evolution strategy(ES) and neural network. We can improve the inherent suspension problem, the trade-off between ride quality and suspension travel by selecting appropriate weight in the LQR-objective function. Since any definite rules for selecting weights do not exist, we replace the designers trial-and-error method with ES that is an optimization algorithm. Using the ES, we can find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle. The relationship between the frequencies and proper control gains are generalized by use of the neural networks. When the vehicle is driven, the trained neural network is activated and provides the proper gains for operating frequencies. And we adopted double sky-hook control to protect car component when passing large bump. Effectiveness of our design has been shown compared to the conventional sky-hook controller through simulation studies.

• Nuclear Engineering and Technology
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• v.26 no.4
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• pp.536-547
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• 1994

The state feedback optimal control techniques are used in designing the reactor control system. The mathematical plant model with the temperature feedback effects is established from the one delayed neutron group point kinetics equation and the singly lumped thermal-hydraulic balance equations, and is expressed in terms of state variables. The LQR (Linear Quadratic Regulator) control system is designed, being followed by the LQG (Linear Quadratic Gaussian) design to determine the optimal conditions of rod movement for the desired reactor power responses. And two different servo control schemes, the ordinary feedback system and the order increased regulating system, are proposed for the purpose of input tacking. The general control characteristics such as stability margins and output responses are discussed. Comparing each other, it is found that the order increased regulating system has far better control characteristics than the ordinary feedback system.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.306-313
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• 2022

Most submarines use the cross-plane, which is convenient and inexpensive, but the number of submarines equipped with an X-plane is increasing recently. This study focuses on designing the control system of the X-plane submarine with various control methods and analyzing the effect of each controller. First, a maneuvering simulation environment for a subjected submarine is established. The dynamics and the operating range of control surfaces are considered. Second, a depth and heading control system of the submarine, which can be divided into three parts, is designed: guidance, controller, and control allocation. The guidance system generates a smooth desired depth and heading. The controller is designed using Proportional-Integral-Differential (PID), Linear Quadratic Regulator (LQR), and H-infinity (H∞) control methods. A linear control allocation method is used to distribute control moment calculated by the controller to the control surfaces. Finally, the designed control system is applied to a subjected X-plane submarine, and a depth and heading control simulations are performed. Each control method is compared and analyzed under various simulation conditions.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.4-75
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• 2001

This paper designs the robust hybrid controller for the multi degree-of-freedom system having uncertainty caused by modeling error and disturbances. The controlled plant is the construction which has an active dynamic vibration absorber on the top and is excited by the El Centre earthquake at the base. The active controller designed by the LQR(Linear Quadratic Regulator) and H-infinity control theory. The robustness of the hybrid H$\infty$ controller is compared with that of the hybrid LQ controller from computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.79-82
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• 1999

The right half plane (RHP) zeros may cause severe problems, such as undershoots, oscillations and time delay in the transient response of the systems. In this paper, we formulate a linear quadratic type problem to deal with the effects of the RHP zeros in the nonminimum phase systems. Based on the LQ formulation, this paper shows the trade-off relation between undershoot and rising time performances in nonminimum phase systems by using a new performance index which consists of new state and tracking error. And performances of the proposed method are shown via computer simulations.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.520-523
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• 2004

A phase-locked loop control system designed by using the linear quadratic regulator approach is presented in this paper. The system thus designed is optimal system when system is in locked state and the parameter value of loop filter which is an active PI filter can be obtained easily. By considering the structure of loop filter of phase-locked loop is included in the process to be controlled, a type 1 servo system can be constructed when voltage control oscillator is considered as an integrator. The integral gain of the proposed system obtained by linear quadratic regulator approach can be used as an optimal value to design the parameter of loop filter. The implemented result in controlling the second-order lag pressure process by using the proposed scheme show that the system response is fast with no overshoot and no steady-state error. Furthermore, the experimental results are also shown in term of output disturbance effect rejection, tracking and process parameter changed.