Constrained Reduced-Order Fractional Kalman Filtering for State Constrained Fractional Linear Systems
This paper is the first to investigate the state filtering problem for linear fractional order discrete state-space systems with state constraints. To tackle this issue, a reduced-order fractional system model is presented by utilizing the linear relationships between state variables and constrains. Afterwards, a constrained reduced-order fractional Kalman filter(CRFKF) is derived accordingly. Last, the effectiveness of the proposed algorithm is demonstrated by a simple tracking example.
Authors
- Jinjian Jiang
- Changgan Zeng (ORCID: https://orcid.org/0000-0001-8630-845X)
- Yong Wang (ORCID: https://orcid.org/0000-0002-4934-9831)
Institutions
- University of Science and Technology of China (CN)
Publication Details
- Published
- 2025-03-21
- DOI
- https://doi.org/10.1109/eect64505.2025.10966944
- Primary Topic
- Advanced Control Systems Design
- Type
- article
- Field-Weighted Citation Impact
- 0.00