지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.10
- 수록면
- 1,840 - 1,844 (5page)
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초록· 키워드
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This paper presents an unmanned quadrotor flight controller, which has its advantages in robust structure and versatile missions, by implementing the dynamic model inversion technique with adaptive neural network. The model inversion of nonlinear dynamic system is conducted via feedback linearization, and the resultant model inversion error is compensated by direct adaptive control. Overall controller adopts PD controller with 2nd order command filter to treat state variables, and neural network is augmented in order to ameliorate the performance of PD controller. To be specific, the type of adaptive controller employed in this paper is Sigma-Pi neural network, considering its simplicity and rapid applicability to online adaptation. Furthermore, the stability of neural network output is guaranteed by Lyapunov stability function. The final designed flight controller is simulated using pre-built quadrotor dynamics. The result of simulation shows the performance of position and attitude control, and can be analyzed with comparison to classical PID controller and model-inversed controller without online neural network.
목차
Abstract
1. INTRODUCTION
2. MODEL INVERSION CONTROL AND ADAPTIVE NEURAL NETWORK
3. DESIGN OF THE CONTROL SYSTEM
4. SIMULATION
5. CONCLUSION
REFERENCES
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