Abstract
Taking the incomplete measurements and the weighted try-once-discard (WTOD) protocol into account, this paper develops a novel resilient set-membership state estimation (RSMSE) method for time-varying nonlinear complex networks with time-invariant delay. A classic interval matrix technique is utilized to describe incomplete measurements. The Taylor series expansion is applied to dispose the nonlinearities, where the high-order terms of the linearization errors are described by norm-bounded uncertainties. To mitigate the communication burden, the WTOD protocol is introduced, where only one node can send updated data through a shared communication network at each certain transmission step. Using the recursive linear matrix inequalities (RLMIs), a series of ellipsoidal sets including the state vector can be determined. The desirable estimator gain and a smallest possible estimation ellipsoid can be calculated via solving the convex optimization problem. Lastly, we use an illustrative example to show the feasibility of the introduced RSMSE technique.
Highlights
Since the end of the 20th century, the state estimation problem of complex networks has been intensively investigated
In response to above comprehensive analyses, this paper focuses on solving the resilient set-membership state estimation (RSMSE) problem for a class of time-varying nonlinear complex networks (TVNCNs) with time-invariant delay and incomplete measurements under the weighted tryonce-discard (WTOD) protocol
The RSMSE problem has been tackled for a class of TVNCNs with timeinvariant delay and incomplete measurements under the WTOD protocol
Summary
Since the end of the 20th century, the state estimation problem of complex networks has been intensively investigated. In [1], the variance-constrained state estimation problem has been concerned for coupled nonlinear complex networks and sufficient criteria have been given to ensure the exponential boundedness of the estimation error in mean-square. There is a special assumption that noise is random and satisfies some probability distributions in the traditional state estimation problem. There is another kind of noise with unknown statistical properties but bounded in the practical system. It is of practical significance to develop the set-membership state estimation (SMSE) approach. A new set-membership filtering recursive scheme of computing the smallest ellipsoid has been exploited in [3] for nonlinear discrete-time systems
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