Paper Info
Title
Dynamic Event-Triggered State Estimation for Continuous-Time Polynomial Nonlinear Systems With External Disturbances
Abstract
This article is concerned with the problem of state estimation for continuous-time polynomial nonlinear (CTPN) systems with unknown but bounded disturbances. The Taylor polynomial expansion technique is employed to realize the conversion from polynomial nonlinear systems to linear-parameter-varying systems related to the estimate. Moreover, for the purpose of saving the communication resources, an event-triggered sampling scheme is first introduced in the state estimation for CTPN systems, where the event-triggered condition is changed dynamically and the Zeno behavior is excluded. Based on the matrix inequality approach, a sufficient condition is derived in terms of the parameter-dependent linear matrix inequality (LMI) such that the estimation error system is input-to-state stable. Then, the desired estimator parameters can be obtained by solving the parameter-dependent LMI via the sum of squares decomposition technique. Finally, two examples with one concerning the permanent magnet synchronous motor systems are provided to demonstrate the usefulness of proposed method.
Year
DOI
Venue
2021
10.1109/TII.2020.3015004
IEEE Transactions on Industrial Informatics
Keywords
DocType
Volume
Continuous-time polynomial nonlinear (CTPN) systems,dynamic event-triggered (DET) scheme,state estimation,sum of squares (SOS),unknown but bounded (UBB) disturbances
Journal
17
Issue
ISSN
Citations 
6
1551-3203
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Yichun Niu183.50
Li Sheng212515.24
Ming Gao3798.36
Dong-Hua Zhou41833129.73