• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.55-59
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• 1991

This paper presents a method for designing a full state feedback linear static control law. This will stabilize a given linear uncertain system and also guarantee the performance of the system. The uncertain systems are described by state equation which contains uncertain parameters in system and input distribution matrices. The method is based on the guaranteed cost control of Chang and Peng(1972). The controller gain can be obtained by the solution of a algebraic Riccati equation in which the input weighting matrices depend on the uncertainty bounds. The algebraic Riecati equation in this paper is same as that of weighted LQ regulator problem.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1049-1054
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• 1990

We formulate optimal quadratic regulator problems with trajectory sensitivity terms as a optimization problem for a fixed controller structure. Using well-known techniques for parametric LQ problems, we give an algorithm to obtain suboptimal feedback gains by iterative solutions of two Lyapunov equations. A numerical example is given to illustrate the effectiveness of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1530-1533
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• 2005

In this paper, we design a Linear Quadratic Gaussian controller for the active suspension. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Because any definite rules for selecting weights do not exist, we use an optimization-algorithm, Evolution Strategy (ES) to find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies. For the full-state feedback control, Kalman filter observes the full states and Fourier transform is used to detect the frequency of the road.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.263-272
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• 2000

In this paper we give some geometric condition for a stochastic nonlinear system and we propose a control method for a stochastic nonlinear system using neural networks. Since a competitive learning neural networks has been developed based on the stochastcic approximation method it is regarded as a stochastic recursive filter algorithm. In addition we provide a filtering and control condition for a stochastic nonlinear system called the perfect filtering condition in a viewpoint of stochastic geometry. The stochastic nonlinear system satisfying the perfect filtering condition is decoupled with a deterministic part and purely semi martingale part. Hence the above system can be controlled by conventional control laws and various intelligent control laws. Computer simulation shows that the stochastic nonlinear system satisfying the perfect filtering condition is controllable and the proposed neural controller is more efficient than the conventional LQG controller and the canonical LQ-Neural controller.

• Journal of Navigation and Port Research
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• v.31 no.6
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• pp.515-521
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• 2007

To increase the stevedore efficiency and service level at container terminal, it is essential to reduce working time of container crane which has a bottle neck in the logistic flow of container. The working speed and safety are required to be improved by controlling the movement of the trolley as quick as possible without big overshoot and any residual swing motion of container in the vicinity of target position. This paper presents optimal state feedback control using RCGAs in the case of existing constrained conditions

• Nuclear Engineering and Technology
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• v.26 no.1
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• pp.32-40
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• 1994

A digital control system for the steam generator oater level control is developed using the optimal control technique. To describe the more realistic situation, a feedwater valve actuator of the first order lag is included in the overall control system. The optimal gains are obtained by the LQ method which imposes the constraints on the feedwater valve motion as well as on the deviation between the input demand signal and the output feedwater. Developed also is a Kalman observer on account of the flow measurement uncertainty at low power. And a digital controller on the feedback loop is designed which makes the system maintain the same stability margins for all power ranges. The simulation results show that the optimal digital system has good control characteristics despite the adverse dynamics of the steam generator at low power.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.503-505
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• 1986

주어진 제어대상 모델에 대하여 제어기를 구성하여 실제로 적용하는 경우 모델의 불일치, 모델링에서 고려하지 않은 외란(disturbance), 측정잡음등에 의하여 성능이 설계시와 달라진다. 실제적용에서도 성능을 계속 유지하기 위하여 제어기는 안정성, 계수변화(parameter variation)에 대한 강인성(robustness), 외란상쇄(disturbance rejection) 및 측정잡음에 둔감함등의 특성을 가져야 한다. 귀환(feedback)을 사용하여 제어기를 구성하는 경우 위의 모든 조건을 만족 시킬 수 없으므로 제어목적에 따라 적당한 조건을 선정하여 중요한 특성을 주로 갖게 한다. 본 논문에서는 쌍동선(small waterplane area twin hull ship-SWATHS)에 대하여 PID, LQ, LQG 제어기를 구성하여 안정성, 계수 변화에 대한 강인성, 외란 상쇄 및 측정잡음의 영향을 비교하였다. 쌍동선의 경우 다른 단동선(mono hull ship)에 비하여 접수면(waterplane)이 적으므로 무게증변을 흡수할 수 있는 복원력이 약하여 적은 외력에도 상하동요(heave)와 종동요(pitch)가 심하게 일어난다. 이러한 동요를 줄이는 것이 쌍동선의 제어목적이다. 본 연구에서는 먼저 선형화된 수직축 운동방정식을 이용하여 선체운동의 모델을 구했으며 중첩의 원리(super-position theorem)에 의하여 주파수 응답의 합으로 파도입력을 모델링 하였으며 제어를 위하여 필요한 측정치는 IMU(Inertial Measurement Unit)에서 제공된다고 가정하였다. 쌍동선의 동요의 원인은 파도, 바람, 조류 등이 있으나 파도에 의한 영향이 가장 크므로 본 논문에서는 파도에 의한 영향만을 고려하였다. 파도는 쌍동선에 외란으로 작용하며 측정할 수 없는 양이므로 PID, LQ 제어에서는 제어모델에 포함되지 않지만 LQG 제어에서는 제어모델에 포함된다. LQG 제어의 경우 제어모델에 파도를 백색잡음으로 가정하고 제어기를 구성한 것 (LQG1)과 2차의 쉐이핑필터(shaping filter)를 사용하여 구성한 것(LQG2)으로 나누었다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2480-2483
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• 2009

This paper presents an LMI-based method to design a integral sliding mode controller for a class of uncertain time-delay systems. Using LMIs we derive an existence condition of a sliding surface guaranteeing the asymptotic stability of the sliding mode dynamics. And we give a switching feedback control law. Our method is a generalization of the previous integral sliding mode control design methods. Since our method is based on LMIs, it gives design flexibility for combining various useful design criteria that can be captured in the LMI-based formulation. We also give LMI existence conditions of sliding surfaces guaranteeing a-stability or LQ performance constraint. Finally, we give a numerical design example to show the effectiveness of the proposed method.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.162-168
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• 2008

A design objective for variable stability flight control system is to develop a controller of in-flight simulation capability that forces the aircraft being flown to follow the dynamics of other aircraft. This paper presents a model-following variable stability control system (VSS) for in-flight simulation which consists of feedforward and feedback control laws, the aircraft dynamic model to be simulated, and switching and fader logics to reduce the transient effect between two aircraft dynamics. The separate design techniques for feedforward and feedback control law proposals are based on model matching and augmented linear quadratic (LQ) techniques. The system allows pilots to select and engage VSS mode, and when deselected, the aircraft reverts to the baseline flight control system. Both the baseline flight control laws and VSS control laws are computed continuously during flight. Initialization of the state values are necessary to prevent instability, since VSS control laws have integrators and filters in longitudinal, and lateral/directional axes. This paper demonstrates and validates the effectiveness and quality of VSS with F-16 models embedded in T-50 in-flight simulation aircraft.

• Journal of Navigation and Port Research
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• v.31 no.10
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• pp.853-858
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• 2007

In this paper, a seesaw system composed with a moving cart on the rail and seesaw frame is made to demonstrate the effectiveness of the control theory. The control aim is to maintain an equilibrium of seesaw frame in spite of various initial conditions and an allowable disturbance. To solve this control problem, a PI-type state feedback controller using reduced-order observer is implemented and applied to the seesaw system. The reduced-order observer can be used to estimate the state variables in the case of the limit of sensor number or the constraint on setting sensors and the cost. A series of simulation are carried out to verify the effectiveness of the control system.