Finite-Time Bounded Functional Observer Design for a Class of Nonlinear Systems

Zhou, Chenglai; Li, Qingbo; Li, Fēi; He, Ping

doi:10.23919/chicc.2018.8482795

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…The H ∞ observer for nonlinear systems with time-delay was designed by FTB method. 23 The FTB functional observer for a class of nonlinear systems 24 was also researched by FTB scheme. However, the controller design problem is more difficult than the observer.…”

Section: Introductionmentioning

confidence: 99%

Finite-time bounded control design for one-sided Lipschitz differential inclusions

Zhou

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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This article considers finite-time bounded controller design for one-sided Lipschitz nonlinear differential inclusions. Sufficient conditions of finite-time bounded criterion are given employing convex hull Lyapunov function approach. An algorithm is designed to calculate the finite-time bounded controller. Moreover, a system initial state selection method is presented to find the domain of system initial state aid for transforming quasi-linear matrix inequality–based conditions to linear matrix inequality-based conditions. Finally, a numerical example and a comparison experiment example are given to illustrate the effectiveness of this proposed design method.

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Section: Introductionmentioning

confidence: 99%

Finite-time bounded control design for one-sided Lipschitz differential inclusions

Zhou

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part I:

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“…In recent years, information science and technology have developed rapidly. [1][2][3][4][5][6][7][8][9][10][11] The field represented by artificial intelligence has achieved fruitful scientific research results. 12,13 Numerous descriptions have been proposed from rigid registration to nonrigid registration.…”

Section: Introductionmentioning

confidence: 99%

A three-dimensional point cloud registration based on entropy and particle swarm optimization

Zhan

Cai

2018

Advances in Mechanical Engineering

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A three-dimensional (3D) point cloud registration based on entropy and particle swarm algorithm (EPSA) is proposed in the paper. The algorithm can effectively suppress noise and improve registration accuracy. Firstly, in order to find the knearest neighbor of point, the relationship of points is established by k-d tree. The noise is suppressed by the mean of neighbor points. Secondly, the gravity center of two point clouds is calculated to find the translation matrix T. Thirdly, the rotation matrix R is gotten through particle swarm optimization (PSO). While performing the PSO, the entropy information is selected as the fitness function. Lastly, the experiment results are presented. They demonstrate that the algorithm is valuable and robust. It can effectively improve the accuracy of rigid registration.

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Finite-Time Bounded Functional Observer Design for a Class of Nonlinear Systems

Cited by 2 publications

References 19 publications

Finite-time bounded control design for one-sided Lipschitz differential inclusions

Finite-time bounded control design for one-sided Lipschitz differential inclusions

A three-dimensional point cloud registration based on entropy and particle swarm optimization

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