TY - GEN
T1 - A fault detection and accommodation framework for dynamic systems with control effector failures
AU - Yang, Hao
AU - Jiang, Bin
AU - Wang, Jian Liang
PY - 2006
Y1 - 2006
N2 - This paper proposes a novel idea that classifies faults into two different kinds: serious fault and small fault, and treats them with different strategies respectively. A kind of artificial neural network (ANN) is proposed for detecting serious faults, and variable structure (VS) model following control is constructed for accommodating small faults. Moreover, the uncertainty case is investigated and the VS controller is modified. Simulation results of a remotely piloted aircraft with control effector failures illustrate the performance of the developed algorithm.
AB - This paper proposes a novel idea that classifies faults into two different kinds: serious fault and small fault, and treats them with different strategies respectively. A kind of artificial neural network (ANN) is proposed for detecting serious faults, and variable structure (VS) model following control is constructed for accommodating small faults. Moreover, the uncertainty case is investigated and the VS controller is modified. Simulation results of a remotely piloted aircraft with control effector failures illustrate the performance of the developed algorithm.
UR - http://www.scopus.com/inward/record.url?scp=33750959435&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:33750959435
SN - 0780393953
SN - 9780780393950
T3 - 1st International Symposium on Systems and Control in Aerospace and Astronautics
SP - 1160
EP - 1165
BT - 1st International Symposium on Systems and Control in Aerospace and Astronautics
T2 - 1st International Symposium on Systems and Control in Aerospace and Astronautics
Y2 - 19 January 2006 through 21 January 2006
ER -