4.7 Article

Zonotopic set-membership estimation for time-varying systems subject to dynamical biases and quantization effects

期刊

INFORMATION SCIENCES
卷 654, 期 -, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2023.119869

关键词

Dynamical biases; Set-membership estimation; Time-varying systems; Uniform quantization; Zonotopes

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This paper studies the problem of zonotopic set-membership estimation (SME) for time-varying systems subject to dynamical biases and uniform quantization. A mathematical method is proposed to estimate the state of the system by analyzing the dynamics of biases and states. An auxiliary zonotope is constructed to minimize the estimation error, and an external approximation is used to reduce the computational burden. The effectiveness of the proposed method is demonstrated through simulations.
In this paper, the zonotopic set-membership estimation (SME) problem is studied for time-varying systems subject to dynamical biases and uniform quantization. The considered dynamical bias evolves according to a certain dynamic process disturbed by unknown-but-bounded noises. The main objective of the paper is to propose a zonotopic SME method such that the real states are included in zonotopes described by linear image of an unit hypercube. By analyzing the dynamics of biases and states, the intersection set containing the state are first obtained based on the quantization measurements. Then, an auxiliary zonotope is constructed to bound the intersection where the center and generator matrix are presented recursively. Through orchestrating the correlation matrix, the F-Radius of such an auxiliary zonotope is further minimized. To reduce the computational burden, the desired zonotope with finite-dimensional generator matrix constructed to externally approximate the auxiliary zonotope. Furthermore, the boundedness stability is analyzed for the developed zonotopic SME approach in the simulations presence of dynamical biases and uniform quantization. Finally, an example is provided to display the effectiveness of the SME method.

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