• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.112-119
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• 2003

Generally, PID controller is not suitable to control multi variable system because it is very difficult to tune the PID gains. However, this paper shows that it is not hard to tune the PID gains if we can find a Jacobian matrix of the system. The Jacobian matrix expresses the ratio of output variations according to input variations. It is possible to adjust the input values in order to reduce the output error using the Jacobian. When the colt function is composed of error related terms, the gradient approach can tune the PID gains to minimize the function. In simulation, a hydrofoil catamaran with two inputs and two outputs is applied as a multi variable system. We can easily get the multi variable PID controller by the proposed teaming method. When the controller is compared with LQR controller, the performance is as good as that of LQR controller with a modeling equation.

• Journal of Astronomy and Space Sciences
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• v.14 no.1
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• pp.142-149
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• 1997

This paper applied one of the well-known optimal control theory, namely, linear quadratic regulator(LQR), to the station-keeping maneuvers(SKM) for a geostationary satellite. The boundary conditions to transfer the system with a good accuracy at a terminal time were based upon the predicted orbital data which are created due to the Earth's non-uniform mass distribution's effect during 14 days and due to luni-solar effect during 28 days. Through the linearization of the nonlinear system equation with respect to reference orbit and the numerical integration of Riccati equation, the optimal trajectories and the corresponding control law have been obtained by using LQR. From the comparison of ${\Delta}V$ obtained by LQR with the ${\Delta}V$ obtained anatically by geometric method, Station Keeping Maneuvers(SKM) via LQR may provide comparable results to a real system. Furthermore it will demonstrate the possibility in fuel optimization and life extension of geostationary satellite.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2493-2496
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• 2003

This paper presents an optimal tuning method of decentralized PID controller of two-input, two-output(TITO) second order system to be formulated as LQR.

• Journal of the Earthquake Engineering Society of Korea
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• v.5 no.6
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• pp.37-46
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• 2001

In this research, a controller design method based on optimization is proposed that can satisfy constraints on maximum responses of building structures subject to around excitation modeled by partially stochastic process. The class of controllers to be optimized is restricted to LQR. Weighting matrix on controlled outputs is used as design variable. Objective function, constraint functions and their gradients are computed by the parameterization of control gain with Riccati matrix. Full state feedback controllers designed by proposed optimization method satisfy various design objectives and their necessary maximum control forces are computed for the production of actuator. LQG controllers composed of Kalman filter and LQR designed by proposed method perform well with little deterioration. So it is possible to design output feedback controllers satisfying constraints on various maximum responses of structures.

• International Journal of Control, Automation, and Systems
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• v.6 no.4
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• pp.506-514
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• 2008

This paper presents an intelligent model; named as free model, approach for a closed-loop system identification using input and output data and its application to design a power system stabilizer (PSS). The free model concept is introduced as an alternative intelligent system technique to design a controller for such dynamic system, which is complex, difficult to know, or unknown, with input and output data only, and it does not require the detail knowledge of mathematical model for the system. In the free model, the data used has incremental forms using backward difference operators. The parameters of the free model can be obtained by simultaneous perturbation stochastic approximation (SPSA) method. A linear transformation is introduced to convert the free model into a linear model so that a conventional linear controller design method can be applied. In this paper, the feasibility of the proposed method is demonstrated in a one-machine infinite bus power system. The linear quadratic regulator (LQR) method is applied to the free model to design a PSS for the system, and compared with the conventional PSS. The proposed SPSA-based LQR controller is robust in different loading conditions and system failures such as the outage of a major transmission line or a three phase to ground fault which causes the change of the system structure.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.1
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• pp.1-9
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• 2014

Structural loading on a wind turbine is due to cyclic loads acting on the blades under turbulence and periodic wind field. The structural loading generates fatigue damage and fatigue failure of the wind turbine. The individual pitch control(IPC) is an efficient control method for reducing structural loading. In this paper, we present an IPC design method using Decentralized LQR(DLQR) and Disturbance accommodating control(DAC). DLQR is used for regulating rotor speed and DAC is used for canceling out disturbances. The performance of the proposed IPC is compared with CPC, which was designed with a gain-scheduled PI controller. We confirm the effect of fatigue load reduction with the use of damage equivalent load(DEL).

• Journal of Mechanical Science and Technology
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• v.15 no.6
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• pp.776-787
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• 2001

The turbofan engine performance analysis for a medium scale commercial aircraft was carried out and the LQR control scheme for performance optimization was studied. By using scaled component maps from well-known CF6 engine characteristics, the steady-state performance analysis result was compared with BR715-56 engine performance data. The transient performance analysis was performed with four fuel schedules. The linear simulation was done at the maximum take-off condition. The real time linear simulation was performed by interpolation of the system matrices, which used the least square method as the function of LPC rotational speed. By using linear system matrices of design point, the LQR controller which used control variables for the fuel flow and the LPC bleed air was designed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.71-76
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• 2008

This paper is concerned with the active vibration control of elevator by means of the active roller guide. To this end, a dynamic model for the horizontal vibration of the elevator consisting of a supporting frame, cage and active roller guides was derived using the energy method. Free vibration analysis was then carried out based on the equations of motion. Active vibration controller was designed based on the equations of motion using the LQR theory and applied to the numerical model. Rail irregularity and wind pressure variation were considered as external disturbance in the numerical simulations. The numerical results show that the active vibration control of elevator is possible.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.111-117
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• 2003

The Taylor model concept is introduced to design a controller with input and output data only. The parameters in Taylor model can be estimated using the input and output data and a controller can be designed based on Taylor model. The accuracy of Taylor model approximation can be improved by increasing the observation window and the order of Taylor model. The LQR method is applied to Taylor model to design power system stabilizers (PSS), and compared with the conventional PSS.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.85-88
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• 2003

강화학습의 한가지 방법인 Q-learning은 최근에 Linear Quadratic Regulation(이하 LQR) 문제에 성공적으로 적용된 바 있다. 특히, 시스템 모델의 파라미터에 대한 구체적인 정보없이 적절한 입ㆍ출력만으로 학습을 통해 문제의 해결이 가능하므로 상황에 따라 매우 실용적인 방법이 될 수 있다. 뉴럴-큐 기법은 이러한 Q-learning의 Q-value를 MLP(multilayer perceptron) 신경망의 출력으로 대치시켜, 비선형 시스템의 최적제어 문제를 다룰 수 있게 한 방법이다. 그러나, 뉴럴-큐 기법은 신경망의 구조를 먼저 결정한 후 역전파 알고리즘을 이용해 학습하는 절차를 행하므로, 시행착오를 통해 신경망 구조를 결정해야 한다는 점, 역전파 알고리즘의 적용에 따라 신경망의 연결강도 값들이 지역적 최적해로 수렴한다는 점등의 문제점이 있다. 본 논문에서는 뉴럴-큐 학습의 도구로 KFD회귀를 이용하여 Q 함수의 근사 기법을 제안하고 관련 수식을 유도하였다. 그리고, 모의 실험을 통하여, 제안된 뉴럴-큐 방법의 적용 가능성을 알아보았다.