4.8 Article

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

Journal

IEEE TRANSACTIONS ON FUZZY SYSTEMS
Volume 29, Issue 11, Pages 3561-3569

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2020.3024659

Keywords

Actuators; Observers; Probability density function; Fuzzy logic; Uncertainty; Fault diagnosis; Fault diagnosis (FD); fault tolerant control (FTC); stochastic distribution control (SDC) systems; sensor and actuator faults; Takagi-Sugeno (T-S) fuzzy model

Funding

  1. Chinese NSF [61973278]

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This article discusses fault diagnosis and fault tolerant control for a class of Takagi-Sugeno fuzzy stochastic distribution control systems, proposing an adaptive observer and fuzzy feedback fault tolerant controller to handle sensor and actuator faults simultaneously.
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.

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