Premium
Unscented Kalman filter for continuous‐time nonlinear fractional‐order systems with process and measurement noises
Author(s) -
Gao Zhe,
Liu Yunting,
Yang Chao,
Chen Xiaojiao
Publication year - 2020
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2077
Subject(s) - unscented transform , kalman filter , control theory (sociology) , extended kalman filter , nonlinear system , discretization , nonlinear filter , noise (video) , filter (signal processing) , invariant extended kalman filter , computer science , mathematics , filter design , artificial intelligence , mathematical analysis , physics , control (management) , quantum mechanics , image (mathematics) , computer vision
This study proposes the design of unscented Kalman filter for a continuous‐time nonlinear fractional‐order system involving the process noise and the measurement noise. The nonlinear fractional‐order system is discretized to get the difference equation. According to the unscented transformation, the design method of unscented Kalman filter for a continuous‐time nonlinear fractional‐order system is provided. Compared with the extended Kalman filter, the proposed method can obtain a more accurate estimation effect. For fractional‐order systems containing non‐differentiable nonlinear functions, the method proposed in this paper is still effective. The unknown parameters are also discussed by the augmented vector method to achieve the state estimation and parameter identification. Finally, two examples are offered to verify the effectiveness of the proposed unscented Kalman filter for nonlinear fractional‐order systems.