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Local nonlinear unknown input observer
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作者 ramzi ben messaoud Mekki KSOURI 《控制理论与应用(英文版)》 EI CSCD 2013年第3期517-520,共4页
This paper proposes a new nonlinear unknown input observer. The observer design approach utilizes the first order Taylor expansion. The observer gains are then obtained by a systematic method. In this paper, we added ... This paper proposes a new nonlinear unknown input observer. The observer design approach utilizes the first order Taylor expansion. The observer gains are then obtained by a systematic method. In this paper, we added some improvements to this method. The developed approach also can enable observer design for a large class of differentiable nonlinear systems. The necessary and sufficient conditions for the existence of the observer are given. A numerical example is given to illustrate the attractiveness and the simplicity of the new design procedure. 展开更多
关键词 Unknown inputs observers STABILITY Nonlinear systems Robust and state estimation
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Nonlinear unknown input observer using mean value theorem and genetic algorithm
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作者 ramzi ben messaoud 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2019年第2期42-63,共22页
In this note,we consider a new unknown input observer design for nonlinear systems.The main idea consists in determining the estimation error and mean value theorem parameters(β)to introduce them into proposed observ... In this note,we consider a new unknown input observer design for nonlinear systems.The main idea consists in determining the estimation error and mean value theorem parameters(β)to introduce them into proposed observer structure.This process is designed on the basis of mean value theorem and genetic algorithm.The stability study relies on the use of a classical quadratic Lyapunov function.The observer’s gains are determined systematically.For the validation of theoretical development proposed in this paper,we consider two practical realizations that deals with the secure communication problem. 展开更多
关键词 Genetic algorithm unknown input observer nonlinear system mean value theorem state estimation
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