Dual Set Membership Filter With Minimizing Nonlinear Transformation of Ellipsoid
| Autor: | Zhiguo Wang, Yunmin Zhu, Xiaojing Shen, Fanqin Meng, Haiqi Liu |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Computer science
Duality (mathematics) Linear system Dynamical Systems (math.DS) Ellipsoid Computer Science Applications Set (abstract data type) Nonlinear system Optimization and Control (math.OC) Control and Systems Engineering Bounded function Dual basis FOS: Mathematics Mathematics - Dynamical Systems Electrical and Electronic Engineering Filter (mathematics) Mathematics - Optimization and Control Algorithm |
| Zdroj: | IEEE Transactions on Automatic Control. 67:2405-2418 |
| ISSN: | 2334-3303 0018-9286 |
| Popis: | In this paper, we propose a dual set membership filter for nonlinear dynamic systems with unknown but bounded noises, and it has three distinctive properties. Firstly, the nonlinear system is translated into the linear system by leveraging a semi-infinite programming, rather than linearizing the nonlinear function. In fact, the semi-infinite programming is to find an ellipsoid bounding the nonlinear transformation of an ellipsoid, which aims to compute a tight ellipsoid to cover the state. Secondly, the duality result of the semi-infinite programming is derived by a rigorous analysis, then a first order Frank-Wolfe method is developed to efficiently solve it with a lower computation complexity. Thirdly, the proposed filter can take advantage of the linear set membership filter framework and can work on-line without solving the semidefinite programming problem. Furthermore, we apply the dual set membership filter to a typical scenario of mobile robot localization. Finally, two illustrative examples in the simulations show the advantages and effectiveness of the dual set membership filter. 26 pages, 9 figures |
| Databáze: | OpenAIRE |
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