• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.856-860
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• 2002

The guaranteed stability margin of LQ optimal regulators with cross-product terms in a performance index is derived for the discrete-time case. In order to obtain the guaranteed stability margin, the singular value of the return difference matrix is examined. A numerical simulation is provided to demonstrate the validity of the derived stability margin.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1996.05a
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• pp.29-37
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• 1996

항공기 가스터빈 엔진은 폭넓은 운용 영역에서 다양한 임무 수행을 하도록 요구되어짐에 따라 항공기 전체의 성능과 직관되는 엔진의 성능에 대한 정밀한 동적 모사와 제어는 매우 중요하다. 본 연구에서는 대표적인 동적 모사 프로그램인 DYNGEN을 이용하여 비선형 동적 모사를 하였고, 이를 바탕으로 엔진의 제어를 위해 비선형 엔진에 대한 Piecewise 선형화를 통해 선형 동적 모사를 수행하였으며, 엔진의 최적 제어 기법으로 LQR 방법을 이용하여 성능 제어를 수행하였다.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.09a
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• pp.419-426
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• 2003

An efficient procedure using LQR method for determining optimal sliding surfaces appropriate for different controller types is provided. The parametric evaluation of the dynamic characteristics of sliding surfaces is peformed in terms of SMC controller performance of single-degree-of-freedom(SDOF) systems. The control force limit is considered in this procedure. Numerical simulations for multi-degree-of-freedom(MDOF) systems verify the effectiveness of proposed method.

• Smart Structures and Systems
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• v.23 no.3
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• pp.243-261
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• 2019

This paper introduces an appropriate technique to estimate the weighting matrices used in the linear quadratic regulator (LQR) method for active structural control. For this purpose, a parameter is defined to regulate the relationship between the structural energy and control force. The optimum value of the regulating parameter, is determined for single degree of freedom (SDOF) systems under seismic excitations. In addition, the suggested technique is generalized for multiple degrees of freedom (MDOF) active control systems. Numerical examples demonstrate the robustness of the proposed method for controlled buildings under a wide range of seismic excitations.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1766-1767
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• 2011

본 논문에서는 기존의 proportional-integral-derivative (PID) 제어기의 이득조정과정에서 linear quadratic regulator(LQR)을 이용하여 이득조정을 하는 방법을 제안한다. 제안된 제어기의 이득은 LQR의 수식으로 표현되어지며 Matlab/simulink을 이용한 모의실험을 통해 위치프로파일에 대한 위치추종오차의 성능이 평가되어진다.

• Wind and Structures
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• v.15 no.3
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• pp.263-283
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• 2012

This paper presents a framework of nonlinear dynamic analysis of a low-speed moving maglev (magnetically levitated) vehicle subjected to cross winds and controlled using a clipped-LQR actuator with time delay compensation. A four degrees-of-freedom (4-DOFs) maglev-vehicle equipped with an onboard PID (Proportional-Integral-Derivative) controller traveling over guideway girders was developed to regulate the electric current and control voltage. With this maglev-vehicle/guideway model, dynamic interaction analysis of a low-speed maglev vehicle with guideway girders was conducted using an iterative approach. Considering the time-delay issue of unsynchronized tuning forces in control process, a clipped-LQR actuator with time-delay compensation is developed to improve control effectiveness of lateral vibration of the running maglev vehicle in cross winds. Numerical simulations demonstrate that although the lateral response of the maglev vehicle moving in cross winds would be amplified significantly, the present clipped-LQR controller exhibits its control performance in suppressing the lateral vibration of the vehicle.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1008-1013
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• 2005

In this paper, position tracking control of an autonomous helicopter is presented. Velocity is controlled by using an optimal state controller LQR. A position control loop is added to form a PD controller. To minimize a position tracking error, neural network is introduced. The reference compensation technique as a neural network control structure is used, and a position tracking error of an autonomous helicopter is compensated by neural network installed in the remotely located ground station. Considering time delays between an autonomous helicopter and the ground station, simulation studies have been conducted. Simulation results show that the LQR with neural network compensation performs better than that of the LQR itself.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.190-196
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• 2014

In this paper, we get state equations based on wheel's rotation, tilt and steering are independent each other in balancing robot. Accordingly, we propose two LQR controllers which are appropriate for rotation and steering control of a balancing robot. And its superiority and appropriateness are demonstrated by a comparison to a PID method. Simulation results verify the possibility of upright balancing, rectilinear motion and position control. Moreover, experimental results show that it guarantees the performance to apply the two LQR controllers to balance the robot.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.1
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• pp.12-20
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• 2002

To control the noise of an enclosed sound field, we built a state space model using the acoustic modal parameter description. Using the state space model, we can investigate the controllability and observability, and find an appropriate position of control speaker and microphone to control sound field of the enclosed space. We implemented LQR(linear quadratic regulator) controller and reduced order observer to reduce the first acoustic mode. Experiments showed satisfactory results of 4∼10 dB reduction of magnitude of the first acoustic mode, and support the feasibility of the proposed scheme to lightly damped acoustic field.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.46-49
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• 2002

This paper presents I-PD controller design using LQR method in a two-inerita motor system to satisfy the design specification in time domain. And to provide a systematic LQ analysis for two-inerita motor system. The tuning parameters of LQ(I-PD) controller are determinated by the relationships between the design parameters of the overshoot and the settling time which are design specifications in time domain, and the weighting factors Q and R in LQR we can achieve the performance-robustness in time domain as well as the stability-robustness.