• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.35-40
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• 1998

A nonlinear attitude model of a satellite with thrusters, magnetic torquers and a reaction wheel cluster is developed. Then the linearized version of this satellite attitude model is derived far the attitude hold mode. For comparison purpose, various control methods are considered for attitude control of a satellite. We consider a proportional derivative controller which is actually used in the remote sensing satellite, KOMPSAT. Then a comparison is made with an H$_2$controller, an H$\sub$$\infty$/ controller, and a mixed H$_2$/ H$\sub$$\infty$/ controller. The analysis and numerical studies show that the proportional derivative controller's performance is limited in the sense that the pitch angle cannot approach zero. The simulations also show that among three control methods (H$_2$control, H$\sub$$\infty$/ control, and mixed H$_2$/ H$\sub$$\infty$/ control) H$_2$control has the fastest response time, H$\sub$$\infty$/ control has the slowest and mixed H$_2$/ H$\sub$$\infty$/ control comes in between the first two control methods. On the other hand, H$\sub$$\infty$/ control used least amount of control effort while H$_2$control required the most.

• 대한임베디드공학회논문지
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• 제15권3호
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• pp.139-148
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• 2020

This paper is concerned with the H₂ attitude controller design for 3 degree of freedom (DOF) Hover systems with an event-triggered mechanism. The 3 DOF Hover system is an embedded platform for unmanned aerial vehicle (UAV) provided by Quanser. The mathematical model of this system is obtained by a linearization around operating points and it is represented as a linear parameter-varying (LPV) model. To save communication network resources, the event-triggered mechanism (ETM) is considered and the performance of the system is guaranteed by the H₂ controller. The stabilization condition is obtained by using Lyapunov-Krasovskii functionals (LKFs) and some useful lemmas. The effectiveness of the proposed method is shown by simulation and experimental results.

• 한국항공우주학회지
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• 제44권1호
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• pp.57-69
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• 2016

폐루프 기준으로 $H_{\infty}$ 제어기를 설계하는 알고리즘에는 3가지(2-ARE, mu-synthesis, LMI) 방법이 있다. 본 논문에서 3가지 $H_{\infty}$ 제어기 설계 알고리즘에 대한 기초 이론을 종합하고, Matlab$^{TM}$에 구현된 함수가 사용될 경우, 실무입장에서 가장 적절하다고 판단되는 $H_{\infty}$ 제어기 설계 알고리즘 제시를 위해 인공위성 자세 제어기 설계 후 결과를 비교 분석하였다: 2-ARE 방법과 LMI 방법은 robust stability, robust performance 및 control authority 측면에서 거의 유사하였으나, LMI 방법에 비해 2-ARE 방법이 weighting 함수설계에 더 민감하였고, mu-synthesis 방법은 다른 2가지 설계 방법에 비해 성능면에서 다소 떨어지고, control authority가 크게 나타났다. 따라서 인공위성 자세제어 설계를 위해 실무 관점에서 LMI 방법이 더 편리한 설계 알고리즘이라는 결론을 얻었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2599-2601
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• 2000

A helicopter control problem has been researched with many control theory. Especially, study of the hovering flight attitude control of a helicopter has been brisked since 60s with multivariable control theory. In this paper, the modeling is interpreted through the 6-freedom equation. To getting a entire equation, species of parameters and charts are adapted. The $H_2/H_{\infty}$ controller is acquired by mixing the $H_2$ control theory and the $H_{\infty}$ control theory. The $H_2$ control theory is reasonable one to increase the performance of a plant, and the $H_{\infty}$ control theory secures the robust stability. The simulation shows that the helicopter system is being controlled while maintaining performance and robust stability against perturbation.

• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.195-203
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• 2016

In order to overcome the influence of system stability and accuracy caused by uncertainty, estimation errors and external disturbances in Eight-Rotor MAV, L2 gain control method was proposed based on interval type II fuzzy neural network identification here. In this control strategy, interval type II fuzzy neural network is used to estimate the uncertainty and non-linearity factor of the dynamic system, the adaptive variable structure controller is applied to compensate the estimation errors of interval type II fuzzy neural network, and at last, L2 gain control method is employed to suppress the effect produced by external disturbance on system, which is expected to possess robustness for the uncertainty and non-linearity. Finally, the validity of the L2 gain control method based on interval type II fuzzy neural network identifier applied to the Eight-Rotor MAV attitude system has been verified by three prototy experiments.