Set-Membership Filtering with Quadratic Inequality Constraints

2019 International Conference on Control, Automation and Information Sciences (ICCAIS)(2019)

Cited 0|Views9
No score
This paper investigates the problem of set-membership filtering for nonlinear dynamic systems with general nonconvex inhomogeneous quadratic inequality constraints. We propose an ellipsoidal state bounding estimation in the setting of unknown but bounded noise. To guarantee the on-line usage, at each time step, the nonlinear function is linearized by Taylor expansion, where the bounding ellipsoid of the remainder is updated on-line based on the current state bounding ellipsoid. Moreover, based on the remainder bounds and the constraints, both the state prediction and measurement update of the filtering can be transformed to a semidefinite programming problem which can be solved efficiently. A typical numerical example demonstrates the effectiveness of this filtering.
Translated text
Key words
Set-membership filter,quadratic inequality constraints,ellipsoidal estimation
AI Read Science
Must-Reading Tree
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined