• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.5
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• pp.78-84
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• 2001

The translation system is made up of springs, masses and a dashpot. This precise piece of equipment is controlled electro-mechanically by a motor and operating program. The control strategy of the system can be changed by spring stiffness, change of mass, and the damping coefficient of the dashpot. This system proves the necessity and effect of a closed loop control. In this paper, PD control experiments were implemented for the translation system. When the north falter was added on the PD controller, we compared the response characteristics of the two systems. The state feedback controller minimized scalar control gains and the resulting response characteristics of the system were studied using the LQR design. Finally, we improved the response characteristics of the translation system which are rising time, settling time, steady state error, and overshoot LQR was better as compared with PD control.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.6
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• pp.98-106
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• 1998

In this study a control law and performance potential of semi-active suspensions for a tractor/semi-trailer have been investigated. The control law for airbag semi-active suspensions modeled in this study is developed using feedback linearization and Linear Quadratic (LQ) optimal control method. Inherent nonlinearity of the airbag suspensions has been considered in the control law development. It has been shown that the proposed semi-active control law provides better performance than that of well known sky-hook damping control strategy.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.19 no.3
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• pp.235-252
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• 2015

Optimal impact angle control guidance law and its variants for intercepting a maneuvering target are introduced in this paper. The linear quadratic(LQ) optimal control theory is reviewed first to setup framework of guidance law derivation, called the sweep method. As an example, the inversely weighted time-to-go energy optimal control problem to obtain the optimal impact angle control guidance law for a fixed target is solved via the sweep method. Since this optimal guidance law is not applicable for a moving target due to the angle mismatch at the impact instant, the law is modified to three different biased proportional navigation(PN) laws: the flight path angle control law, the line-of-sight(LOS) angle control law, and the relative flight path angle control law. Effectiveness of the guidance laws are verified via numerical simulations.

• Journal of Wind Energy
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• v.2 no.1
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• pp.74-81
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• 2011

This paper deals with the application of LQ control to the power curve tracking control of wind turbine. However, two more additional tasks are required to apply the LQR theory to wind turbine control. One is the tracking problem instead of regulation, because the wind turbine is controlled as variable speed and variable pitch. The other is LQ integral control., because the rotor speed should be tightly controlled without any steady state error. Starting from the analysis of wind characteristics, design requirement of a wind turbine control system is defined. A design procedure of LQ tracking with integral control is introduced. The performance of LQ tracking system is analyzed and evaluated by numeric simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1091-1094
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• 1996

The Object of this study is to find the relations between LQR and eigenstructure assignment regulator. Algorithms for computing weighting matrices are proposed for the case that (i) closed-loop eigenvalues are specified, and (ii) closed-loop gain matrix is given. We also present a new eigenstructure assignment algorithm that minimizes a linear quadratic performance index.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.125-128
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• 2004

Q-learning은 강화학습의 한 방법으로서, 여러 분야에 널리 응용되고 있는 기법이다. 최근에는 Linear Quadratic Regulation (이하 LQR) 문제에 성공적으로 적용된 바 있다. 특히 시스템 모델의 파라미터에 대한 구체적인 정보가 없는 상태에서 적절한 입력과 출력만을 가지고, 학습을 통해 문제를 해결할 수 있어서 상황에 따라서 매우 실용적인 대안이 될 수 있다. 이에 따라 본 논문에서는 이러한 일반적인 LQR Q-learning(이하 LQRQL) 학습방법에 퍼지 모델을 이용하여 제어기를 설계하는 방법을 고려하고, 일반적인 LQROL 기법과 본 논문에서 제시한 방법의 결과를 비교하여 응용 가능성을 살펴보았다.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.407-410
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• 1989

Optimizing transient response for both tracking reference signals and disturbance rejection is determined by the poles and zeros of the transfer function. Thus, optimal pole assignment and how should weighting matrix for the performance index be chosen is very important to achieve optimum transient response. This paper focus its attention on the choosing and analysis of weighting matrix for optimum pole assignment. Optimum pole assignment is defined for linear time-invariant continuous systems.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.9
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• pp.920-928
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• 1991

This paper proposes a design procedure based on the LQG/LTR (Linear Quadratic Gaussian/ Loop Transfer Recovery) method for a launch vehicle. Continuous-discrete type LQG/LTR compensators are designed using the e-transformation to overcome numerical problems occurring in the process of discretization. The e-LQG/LTR compensator using the e-transformation is compared width the z-LQG/LTR compensator using the z-transformation. The performance of the overall system controlled by the compensator is evaluated via simulations, which show that the discretization error problem is resolved and the control performances are satisfactory in the proposed compensator.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.91-94
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• 1985

A method optimizing selection of a state weighting matrix is presented. The state weight-ing matrix is chosen so that the closed-loop system responses closely match to the ideal model responses. An algorithm is presented which determines a positive semidefinite state weighting matrix in the linear quadratic optimal control design problem and an numerical example is given to show the effect of the present algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.373-378
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• 1998

A method to construct a memoryless feedback law for systems with multiple time-delays in the states is proposed. As a plant model, a differential-difference equation with multiple delayed terms is introduced, A stabilizability condition by memoryless feedback is presented. A feedback gain is calculated with a solution of a finite dimensional Riccati equation. It is shown that the resulting closed loop system is asymptotically stable, and moreover, it is a linear quadratic regulator for some cost functional. An alternative stabilizability condition which is easier to check is given.