Two-Dimensional Peak-to-Peak Filtering for Stochastic Fornasini-Marchesini Systems

This paper is concerned with the problem of two-dimensional (2-D) stochastic peak-to-peak filter design for Fornasini-Marchesini local state-space (FM LSS) systems with state-multiplicative noise. First, a novel sufficient condition is established, which guarantees that the underlying FM LSS system...

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Bibliographic Details
Published in:IEEE transactions on automatic control 2018-05, Vol.63 (5), p.1472-1479
Main Authors: Choon Ki Ahn, Peng Shi, Basin, Michael V.
Format: Article
Language:English
Subjects:
Boundary conditions
Fornasini–Marchesini local state-space (FM LSS) model
Frequency modulation
Integrated circuit modeling
Niobium
Numerical models
stochastic peak-to-peak filtering
Stochastic processes
Symmetric matrices
two-dimensional (2-D) systems
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Summary:This paper is concerned with the problem of two-dimensional (2-D) stochastic peak-to-peak filter design for Fornasini-Marchesini local state-space (FM LSS) systems with state-multiplicative noise. First, a novel sufficient condition is established, which guarantees that the underlying FM LSS system is stochastically mean-square stable with 2-D stochastic peak-to-peak performance. A deterministic FM LSS system case is also discussed. Subsequently, based on the result, a new 2-D stochastic peak-to-peak filter of general form is designed for FM LSS systems with state-multiplicative noise. Finally, a numerical example is presented to show the effectiveness of the proposed 2-D stochastic peak-to-peak filter.
ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2017.2747761