• Journal of the Korean Society for Precision Engineering
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• v.18 no.1
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• pp.56-62
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• 2001

In this paper, skyhook control of a semi-active ER(Electro-Rheological) damper is investigated. The strength of the ER damper is controlled by a high voltage power supply. This paper deals with a two-degree-of-freedom suspension using the damper with ERF for a quarter vehicle system. The control law for semi-active suspensions modeled in this study is developed using skyhook and Linear Quadratic Regulator(LQR) optimal control method. Computer simulation and experimental results show that the semi-active suspension with ERF damper has good performances of ride quality.

• Proceedings of the Korean Institute of Surface Engineering Conference
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• 2009.10a
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• pp.229-230
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• 2009

본 연구에서는 플라즈마 기본 변수인 전자밀도, 전자온도, 그리고 이온 유량을 제어하는 조정기를 설계하였다. 플라즈마 증착장비를 이용하여 상온에서 SiN 박막을 증착하는 과정에서 in-situ 센서인 Wise Probe를 이용하여 데이터를 수집하였다. 수집된 데이터를 이용하여 플라즈마 확인 (Identification) 모델을 개발하고, 이를 이용하여 Linear Quadratic Regulator를 설계하였다. Noise와 Disturbance에 대한 응답특성을 고찰하였으며, 설계된 Regulator는 비교적 안정된 반응을 보였다.

• 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.

• Journal of Industrial Technology
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• v.10
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• pp.3-8
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• 1990

This paper presents a linear state feedback control approach to the stabilization of discrete-time uncertain systems with bounded uncertain parameters. The approach is based on the LQ(linear quadratic) regulator theory and Lyapunov's stability analysis. Asymptotically stable behavior is guaranteed in the presence of parameter uncertainties, and the upper bound of the performance index is determined.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.6
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• pp.505-516
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• 2011

The concept of the IGC(Integrated Guidance and Control) has been introduced to overcome the performance limit of the SGC(Separated Guidance and Control) loop. A new type of IGC with impact angle constraint has been proposed in this paper. Angle of attack, pitch angle rate, pitch angle and line of sight angle are considered as state variables. A controllability analysis and equilibrium point analysis have been carried out to investigate the control characteristic of the prposed IGC. The LQR(Linear Quadratic Regulator) has been adopted for the control law and detailed explanations about the adoption has been provided. The performance comparison between the IGC and the SGC has been carried out. The result of numerical simulations shows that the IGC guarantees better guidance performance than the SGC when the agile maneuver is needed for a specific guidance geometry.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.9
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• pp.749-757
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• 2021

In transportation missions using quadrotor, the payload may change the model parameters, such as mass, moment of inertia, and center of gravity. Moreover, if position of the payload is constantly changing during flight, the effect can adversely affect the control performances. To handle this issue, we suggest Model Reference Adaptive Control based on Linear Quadratic Regulator(LQR+MRAC) to compensate the uncertainty caused by payload. Firstly, the mathematical modeling with the fixed payload is derived. Second, Linear Quadratic Regulator (LQR) is used to design the reference model and baseline controller. Also, through the Stability method, Adaptive law is derived to estimate the model parameters. To verify the performance of proposed control scheme, we compared LQR and LQR+MRAC in situations where uncertainties exist. And, when the disturbance exist, the classic MRAC and proposed controller is compared to analyze the transient response and robustness.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.79-83
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• 2000

Although it is well known that fuzzy learning controller is powerful for nonlinear systems, it is very difficult to apply a learning method if they are unstable. An unstable system diverges for impulse input. This divergence makes it difficult to learn the rules unless we can find the initial rules to make the system table prior to learning. Therefore, we introduced LQR(Linear Quadratic Regulator) technique to stabilize the system. It is a state feedback control to move unstable poles of a linear system to stable ones. But, if the system is nonlinear or complicated to get a liner model, we cannot expect good results with only LQR. In this paper, we propose that the LQR law is derived from a roughly approximated linear model, and next the fuzzy controller is tuned by the adaptive on-line learning with the real nonlinear plant. This hybrid controller of LQR and fuzzy learning was superior to the LQR of a linearized model in unstable nonlinear systems.

• 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.

• Structural Engineering and Mechanics
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• v.18 no.3
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• pp.287-301
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• 2004

Structural acceleration regulation is a means of managing structural response energy and enhancing the performance of civil structures undergoing large seismic events. A quadratic output regulator that minimizes a measure including the total structural acceleration energy is developed and tested on a realistic non-linear, semi-active structural control case study. Suites of large scaled earthquakes are used to statistically quantify the impact of this type of control in terms of changes in the statistical distribution of controlled structural response. This approach includes the impulses due to control inputs and is shown to be more effective than a typical displacement focused control approach, by providing equivalent or better performance in terms of displacement and hysteretic energy reductions, while also significantly reducing peak story accelerations and the associated damage and occupant injury. For earthquake engineers faced with the dilemma of balancing displacement and acceleration demands this control approach can significantly reduce that concern, reducing structural damage and improving occupant safety.

• Bulletin of the Korean Space Science Society
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• 1996.11a
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• pp.19-19
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• 1996

No Abstract, See Full Text