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Active fault tolerant control systems by the semi‐Markov model approach
Author(s) -
Huang Ji,
Shi Yang,
Zhang Xue
Publication year - 2014
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/acs.2401
Subject(s) - control theory (sociology) , controller (irrigation) , markov chain , markov process , fault tolerance , actuator , process (computing) , fault (geology) , control engineering , convex optimization , stability (learning theory) , computer science , markov model , markov decision process , engineering , fault detection and isolation , regular polygon , control (management) , distributed computing , mathematics , artificial intelligence , statistics , geometry , machine learning , seismology , agronomy , biology , geology , operating system
SUMMARY This paper investigates the active fault tolerant control problem via the H ∞ state feedback controller. Because of the limitations of Markov processes, we apply semi‐Markov process in the system modeling. Two random processes are involved in the system: the failure process and the fault detection process. Therefore, two corresponding semi‐Markov processes are integrated in the closed‐loop system model. This framework can generally accommodate different types of system faults, including the randomly happening sensor faults and actuator faults. A controller is designed to guarantee the closed‐loop system stability with a prescribed noise/disturbance attenuation level. The controller can be readily solved by using convex optimization techniques. A vertical take‐off and landing vehicle example with actuation faults is used to demonstrate the effectiveness of the proposed technique. Copyright © 2013 John Wiley & Sons, Ltd.