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Networked gain‐scheduled fault diagnosis under control input dropouts without data delivery acknowledgment
Author(s) -
Dolz Daniel,
Peñarrocha Ignacio,
Sanchis Roberto
Publication year - 2015
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.3335
Subject(s) - control theory (sociology) , residual , observer (physics) , computer science , fault detection and isolation , fault (geology) , statistic , jump , controller (irrigation) , mathematics , mathematical optimization , control (management) , algorithm , actuator , statistics , artificial intelligence , physics , quantum mechanics , seismology , agronomy , biology , geology
Summary This paper investigates the fault diagnosis problem for discrete‐time networked control systems under dropouts in both control and measurement channel with no delivery acknowledgment. We propose to use a proportional integral observer‐based fault diagnoser collocated with the controller. The observer estimates the faults and computes a residual signal whose comparison with a threshold alarms the fault appearance. We employ the expected value of the arriving control input for the open‐loop estimation and the measurement reception scenario for the correction with a jump observer. The jumping gains are scheduled in real time with rational functions depending on a statistic of the difference between the control command being applied in the plant and the one being used in the observer. We design the observer, the residual, and the threshold to maximize the sensitivity under faults while guaranteeing some minimum detectable faults under a predefined false alarm rate. Exploiting sum‐of‐squares decomposition techniques, the design procedure becomes an optimization problem over polynomials. Copyright © 2015 John Wiley & Sons, Ltd.