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Fault estimation and synchronization control for complex dynamical networks with time‐varying coupling delay
Author(s) -
Sakthivel Rathinasamy,
Sakthivel Ramalingam,
Kwon OhMin,
Kaviarasan Boomipalagan
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5388
Subject(s) - control theory (sociology) , observer (physics) , computer science , estimator , synchronization (alternating current) , fault (geology) , state (computer science) , set (abstract data type) , bounded function , matching (statistics) , coupling (piping) , control (management) , mathematics , algorithm , engineering , mechanical engineering , computer network , mathematical analysis , channel (broadcasting) , statistics , physics , quantum mechanics , artificial intelligence , seismology , programming language , geology
This article is devoted to simultaneously solve the problems of fault estimation and synchronization for a class of delayed coupling complex dynamical networks. First, an intermediate estimator is established for each node with the aid of the relative information from the neighboring nodes. Second, a distributed memory state feedback controller is designed with respect to the estimated state values and fault signals. Third, some error systems are formulated by introducing appropriate linear transformations. Then, a set of delay‐dependent criteria is obtained to ensure that the states of the resulting systems are uniformly bounded and subsequently, the explicit design method of the desired gain matrices is presented. At last, the feasibility of established theoretical results is validated by the support of two numerical examples in which one is an application example based on the aircraft model. Different from the existing fault estimation techniques, the proposed method does not require the observer matching condition and the upper bounds of the fault signals, which reduces the conservatism significantly.