TY - GEN
T1 - Fuzzy modeling-based fault diagnosis and fault tolerant control for the non-Gaussian nonlinear singular stochastic distribution system
AU - Li, Lifan
AU - Lei, Chunhui
AU - Yao, Lina
AU - Zhou, Jinglin
AU - Wang, Hong
N1 - Publisher Copyright:
© 2018 AACC.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - In this paper, a new fault diagnosis and fault tolerant control (FTC) algorithm is presented for the non-Gaussian nonlinear singular stochastic distribution control (SDC) system based on fuzzy modeling. Linear fuzzy logic models are used to approximate the output probability density function (PDF) and Takagi-Sugeno fuzzy models are employed to describe the nonlinear relations between fuzzy weight dynamics and the control input. Fault diagnosis is based on the use of a fuzzy fault diagnosis observer, with which the fault can be diagnosed. Based on the estimated fault and the desired PDF information, a fuzzy fault tolerant controller is designed to make the postfault PDF still track the given distribution. At last, simulation results on a flame shape distribution control system is given to demonstrate the effectiveness of the proposed algorithm, and satisfactory results have been obtained.
AB - In this paper, a new fault diagnosis and fault tolerant control (FTC) algorithm is presented for the non-Gaussian nonlinear singular stochastic distribution control (SDC) system based on fuzzy modeling. Linear fuzzy logic models are used to approximate the output probability density function (PDF) and Takagi-Sugeno fuzzy models are employed to describe the nonlinear relations between fuzzy weight dynamics and the control input. Fault diagnosis is based on the use of a fuzzy fault diagnosis observer, with which the fault can be diagnosed. Based on the estimated fault and the desired PDF information, a fuzzy fault tolerant controller is designed to make the postfault PDF still track the given distribution. At last, simulation results on a flame shape distribution control system is given to demonstrate the effectiveness of the proposed algorithm, and satisfactory results have been obtained.
UR - http://www.scopus.com/inward/record.url?scp=85052561685&partnerID=8YFLogxK
U2 - 10.23919/ACC.2018.8431786
DO - 10.23919/ACC.2018.8431786
M3 - Conference contribution
AN - SCOPUS:85052561685
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 5781
EP - 5786
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Annual American Control Conference, ACC 2018
Y2 - 27 June 2018 through 29 June 2018
ER -