Fault Diagnosis and Fault Tolerant Control for T-S Fuzzy Stochastic Distribution Systems Subject to Sensor and Actuator Faults

• Published in: IEEE transactions on fuzzy systems Vol. 29; no. 11; pp. 3561 - 3569
• Main Authors: Wang, Hao, Kang, Yunfeng, Yao, Lina, Wang, Hong, Gao, Zhiwei
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Algorithms; Chemical reactions; Control systems design; Controllers; Fault diagnosis; Fault diagnosis (FD); Fault tolerance; Fault tolerant control; fault tolerant control (FTC); Fuzzy control; Fuzzy logic; Fuzzy systems; Observers; Probability density functions; sensor and actuator faults; Sensors; stochastic distribution control (SDC) systems; Takagi-Sugeno model; Takagi–Sugeno (T–S) fuzzy model; Uncertainty
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2020.3024659

The problem of fault diagnosis (FD) and fault tolerant control for a class of Takagi-Sugeno (T-S) fuzzy stochastic distribution control systems subject to sensor and actuator faults is discussed in this article. First, fuzzy logic models are used to approximate the output probability density function (PDF). Next, an adaptive augmented state/FD observer is proposed to estimate the system state, sensor and the actuator faults simultaneously. New expected weights based on the sensor fault estimation information and a PI-type fuzzy feedback fault tolerant controller are designed to compensate the effect of sensor fault and actuator fault simultaneously. When the sensor fault occurs, the expected objective is redesigned to compensate the sensor fault. Meanwhile, the PI controller can compensate the effect of actuator fault, and the output PDF of the system can still track the desired PDF after the fault occurs. Finally, an example of quality distribution control in chemical reaction process is given to confirm the effectiveness of the algorithm.