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
- 2004.10
- 수록면
- 513 - 517 (5page)
이용수
초록· 키워드
오류제보하기
A robustly adaptive speed sensorless direct vector control system using a neural network (NN) is presented in this paper. Firstly, a new type of flux observer based on a robust control scheme is introduced. The uncertainty of the rotor resistance mainly affects the speed estimation performance, and until now, various observer approaches have been developed. The proposed flux observer employs an additional robustifying signal to cope with the uncertainty instead of the resistance adaptation procedure. The proposed adaptive scheme is determined so that the observer dynamics is stable in the sense of Lyapunov. Secondly, a robust speed controller using a NN is proposed. The lumped uncertainties including parametric uncertainty, external load disturbance and unmodeled dynamics are approximated by the NN, and an additional robust control term is introduced to compensate for the reconstruction error of the NN. A control law and adaptive laws for the weights in the NN and a bounding constant are established so that t closed-loop system is stable in the sense of Lyapunov. Some computer simulations are presented to show the efficiency of the proposed system.
목차
Abstract
Ⅰ. INTRODUCTION
Ⅱ. ROBUSTLY ADAPTIVE FLUX OBSERVER
Ⅲ. INDUCTION MOTOR SPEED CONTROL SYSTEM
Ⅳ. ROBUSTLY STABLE SENSORLESS SPEED CONTROLLER USING THE RBFN
Ⅴ. SIMULATIONS
Ⅵ. CONCLUSIONS
REFERENCES
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UCI(KEPA) : I410-ECN-0101-2009-560-014561308