High-Order Extended Kalman Filter Design for a Class of Complex Dynamic Systems with Polynomial Nonlinearities

被引:13
作者
Sun Xiaohui [1 ]
Wen Chenglin [1 ,2 ]
Wen Tao [3 ]
机构
[1] Hangzhou Dianzi Univ, Sch Automat, Hangzhou 310018, Peoples R China
[2] Guangdong Univ Petrochem Technol, Sch Automat, Maoming 525000, Peoples R China
[3] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
基金
中国国家自然科学基金;
关键词
High-order extended Kalman filter; Nonlinear systems; Implicit variables; Pseudo-linear; Polynomial nonlinearity; STATE ESTIMATION;
D O I
10.1049/cje.2021.04.004
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A novel High-order extended Kalman Filter (HEKF) is designed for a class of complex dynamic systems with polynomial nonlinearities. The state and measurement models are represented by multi-dimensional high-order polynomials, respectively. All high-order polynomials in the state model are defined as implicit variables. By combining original variables with implicit variables, the state model is equivalently formulated to be a pseudo-linear form. By modeling dynamic relationship between implicit variables and combining original variables with all implicit variables, a new linear augmented state model is established correspondingly. The measurement model can be equivalently formulated as a linear form. On the basis of the new linear state and linear measurement models, the HEKF is designed and derived in detail. Simulation results demonstrate the effectiveness of the proposed estimator.
引用
收藏
页码:508 / 515
页数:8
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