• 대한기계학회논문집A
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• 제38권1호
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• pp.1-9
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• 2014

로터에 작용하는 불균형한 반복 하중은 풍력발전기에 구조적 하중을 발생시키고 이러한 하중이 구조물에 지속적으로 누적되면 피로 파괴와 수명 단축을 발생시킨다. Individual pitch control(IPC)는 이러한 구조적 하중을 저감시키고 풍력발전기의 작동 수명 연장에 효과가 있는 제어 방법이다. 본 연구에서는 Decentralized LQR(DLQR)과 Disturbance accommodating control(DAC)를 이용한 IPC 설계를 제시한다. DLQR은 로터 회전속도 제어를 위해 사용하였고 DAC는 블레이드에 외란으로 작용하는 바람(난류) 효과를 상쇄하도록 구성하였다. 제시된 IPC제어기의 구조적 하중 저감 효과는 Gain-scheduled PI로 설계된 Collective pitch control(CPC)과 비교하여 확인하였다. 또한, IPC의 구조물 하중 저감 효과를 확인하기 위해 피로 누적에 의한 손상정도를 나타내는 피로등가하중(DEL)을 이용하였다.

• 대한조선학회논문집
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• 제49권1호
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• pp.14-25
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• 2012

Recently, the application and installation of the pod propeller to the cruise ship is dramatically increased. It is because pod propulsion system allows a lot of flexibility in design of the internal arrangement of a ship. To reflect this trend, many researches have conducted to use the pod propeller for the roll stabilization of a ship. In the paper, a roll stabilization controller is designed by using fins and pod propellers as the control actuators for cruise ships. Two kinds of control algorithms are adopted for the roll control system; LQR (Linear Quadratic Regulator) algorithm and frequency-weighted LQR algorithm. Through the numerical simulation, the effect of the turning rate of the pod propeller on the roll control system is analyzed. Analysis of the simulation results indicated that the turning rate of the pod propellers is one of the important parameters which give the significant effects on the roll stabilization.

• 한국항해학회지
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• 제23권3호
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• pp.35-44
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• 1999

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

• 한국산업융합학회 논문집
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• 제2권1호
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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.

• 전자공학회논문지SC
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• 제41권2호
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• pp.1-8
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• 2004

본 논문은 시간지연을 갖는 2차 시스템에서 시간영역의 설계사양을 만족하는 최적 강인 LQ-PID제어기 설계방법을 제안한다. 시간지연을 갖는 2차 시스템의 LQR 해를 이용한 LQ-PID제어기 파라미터는 설계사양을 만족하는 가격함수의 가중치요소 C와 R에 의해 결정되고, Q와 R의 선정은 시간영역에서의 오버슈트와 정착시간을 조절할 수 있는 설계파라미터들 선정에 의해 결정되어진다.

• 산업기술연구
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• 제18권
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• pp.303-308
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• 1998

In this paper a neural network controller called "Feedback-State Learning" for control of the attitude of a wheeled inverted pendulum is presented. For the controller the design of a stable feedback controller is necessary, so the LQR is used for the feedback controller because the LQR has good performance on controlling nonlinear systems. And the neural networks are used for a feed forward controller. The designed controller is applied to the stabilization of a wheeled inverted pendulum. Because of its nonlinear characteristics such as friction and parameter variations in the linearization, the wheeled inverted pendulum is used for demonstration of the effectiveness of the proposed controller.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2170-2172
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• 2003

This paper presents the position tracking control of an inverted pendulum on an inclined railway. In general, inclining the railway leads to errors in the pendulum angle even though the pendulum is stabilized, which results in errors in the cart position. To solve this problem, a linear quadratic regulation (LQR) controller with an integrator is used for compensating the resulting error in the cart position. The proposed method is evaluated by comparing LQR controllers with and without an integrator. Experimental results show that the LQR controller with an integrator is better in performance than one without an integrator.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2000년도 봄 학술발표회논문집
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• pp.431-438
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• 2000

The cost function consists of the weighting functions concerning the structural responses to be controlled and the controller capability. Therefore, the control efficiency depends on the characteristics of the weighting functions. The objective of this paper is the comparative study of the time domain control strategies of LQR and LQG and the frequency domain strategy of H₂ by setting the equivalent weighting functions to the all control strategies. As a result of analysis, LQR strategy is found to be more efficient than other strategies in terms of the response reduction. but the control force is found to be a little highter. As LQG can compensate the limitation of LQR that all state variables should be identified, LQG is more acceptable algorithm than LQR. Furthermore LQG shows a good performance both in the response reduction and the control force. Finally H₂ algorithm is employed to illustrate the importance of weighting filters considering the frequency characteristics of the response and the controller. It Is shown that the H₂ algorithm is found to be the most effective one for the response control with a little control force having a low frequency band.

• 한국군사과학기술학회지
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• 제12권4호
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• pp.540-547
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• 2009

In the near future, military robots are likely to be substituted for military personnel in the field of battle. The power system of a legged robot is considerably more complex than the one used for a land vehicle because of the coordination and stability issues due to the large number of degree of freedom. In this paper, a servovalve-piston combination system for a straight-line motion of robot leg is modeled as three degree of freedom based on double inputs and single output transfer function. The output is the displacement of piston from neutral. The inputs are valve displacement from neutral and arbitrary load force in this system. LQR(Linear Quadratic Regulator) technique is applied in order to achieve robust stability and fast responses of the system. The Kalman filter loop, rejection of disturbance and noise, riccati equation, filter gain matrix, and frequency domain equality are analyzed and designed.

• Nuclear Engineering and Technology
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• 제26권4호
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• pp.536-547
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• 1994

본 논문에서는 최적제어기법을 이용한 원자로 출력 제어시스템을 다루었다. 시스템 변수들을 상태변수로 표시하면 관측치 뿐만 아니라 시스템 내부의 모든 상태변수를 동시에 다룰 수 있으므로 설계의 자유도가 증가될 수 있다. 따라서 본 논문에서는 원자로의 동특성식과 열수력학적 에너지 평형식을 사용하여 원자로를 모델링한 후 이를 상태변수로 나타내었다. 다음으로는 LQR 및 LQG 시스템을 설계하여 제어봉 및 출력의 거동을 동시에 만족시킬 수 있는 설계조건을 결정하였다. 또한 서보 시스템의 설계를 위해 보통의 휘드백 시스템과 차수를 증가시킨 레귤레이팅 시스템을 만들어 비교하였으며 그 결과 증가차수 레귤레이팅 시스템이 보통의 휘드백 시스템에 비해 우수한 제어 특성이 있음을 알 수 있었다.