Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)
- 2001.07d
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- Pages.2320-2322
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- 2001
Robust Adaptive Neural-Net Observer for Nonlinear Systems Using Filtering of Output Estimation Error
출력관측 오차의 필터링을 이용한 비선형 계통의 강인한 신경망 관측기 설계
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Park, Jang-Hyun
(School of Electrical Engineering, Korea Univ.) ;
- Yoon, Pil-Sang (School of Electrical Engineering, Korea Univ.) ;
- Park, Gwi-Tae (School of Electrical Engineering, Korea Univ.)
- Published : 2001.07.18
Abstract
This paper describes the design of a robust adaptive neural-net(NN) observer for uncertain nonlinear dynamical system. The Lyapunov synthesis approach is used to guarantee a uniform ultimate boundedness property of the state estimation error, as well as of all other signals in the closed-loop system. Especially, for reducing the dynamic oder of the observer, we propose a new method in which no strictly positive real(SPR) condition is needed with on-line estimation of weights of the NNs. No a priori knowledge of an upper bounds on the uncertain terms is required. The theoretical results are illustrated through a simulation example.
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