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Set-membership fuzzy filtering for nonlinear discrete-time systems
journal contributionposted on 2017-12-06, 00:00 authored by Fuwen YangFuwen Yang, Y Li
This paper is concerned with the set-membership filtering (SMF) problem for discrete-time nonlinear systems. We employ the Takagi–Sugeno (T-S) fuzzy model to approximate the nonlinear systems over the true value of state and to overcome the difficulty with the linearization over a state estimate set rather than a state estimate point in the set-membership framework. Based on the T-S fuzzy model, we develop a new nonlinear SMF estimation method by using the fuzzy modeling approach and the S-procedure technique to determine a state estimation ellipsoid that is a set of states compatible with the measurements, the unknown-but-bounded process and measurement noises, and the modeling approximation errors. A recursive algorithm is derived for computing the ellipsoid that guarantees to contain the true state. A smallest possible estimate set is recursively computed by solving the semidefinite programming problem. An illustrative example shows the effectiveness of the proposed method for a class of discrete-time nonlinear systems via fuzzy switch.
Category 1 - Australian Competitive Grants (this includes ARC, NHMRC)
Number of Pages9
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External Author AffiliationsBrunel University; Hua dong li gong da xue; TBA Research Institute;