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Detection, estimation, and accommodation of loss of control effectiveness
Author(s) -
Eva Wu N.,
Zhang Youmin,
Zhou Kemin
Publication year - 2000
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/1099-1115(200011)14:7<775::aid-acs621>3.0.co;2-4
Subject(s) - accommodation , estimation , computer science , control (management) , control theory (sociology) , artificial intelligence , engineering , psychology , systems engineering , neuroscience
Abstract In this paper, an adaptive Kalman filtering algorithm is developed for use to estimate the reduction of control effectiveness in a closed‐loop setting. Control effectiveness factors are used to quantify faults entering control systems through actuators. A set of covariance‐dependent forgetting factors is introduced into the filtering algorithm. As a result, the change in the control effectiveness is accentuated to help achieve a more accurate estimate more rapidly. A weighted sum‐squared bias estimate is defined for the change detection. The state estimate is fed back to achieve the steady‐state regulation, while the control effectiveness estimate is used for the on‐line tuning of the control law. A stability analysis is performed for the adaptive regulator. Copyright © 2000 John Wiley & Sons, Ltd.