Observer-Based Fault Reconstruction and Fault-Tolerant Control for Nonlinear Systems Subject to Simultaneous Actuator and Sensor Faults

• Published in: IEEE transactions on fuzzy systems Vol. 30; no. 8; pp. 2971 - 2980
• Main Authors: Zhang, Huaguang, Mu, Yunfei, Gao, Zhiyun, Wang, Wei
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Actuators; Control systems; Fault estimation (FE); Fault tolerance; Fault tolerant systems; fault-tolerant control (FTC); Faults; fuzzy Lyapunov function; Fuzzy systems; Iron; Liapunov functions; Lyapunov methods; Nonlinear control; Nonlinear systems; Observers; Reconstruction; Sensors; Stability criteria; Takagi–Sugeno (T-S) fuzzy model; unknown input observer (UIO)
• ISSN: 1063-6706; 1941-0034
• DOI: 10.1109/TFUZZ.2021.3098341

In this article, we pay our attention on exploring observer-based actuator fault and sensor fault reconstruction associated with fault-tolerant control (FTC) for nonlinear systems, which are approximated by the Takagi-Sugeno (T-S) fuzzy method. By designing a brand-new unknown input observer (UIO), unknown state, sensor, and actuator faults can be reconstructed simultaneously, where some constraints imposed on the actuator fault such as the first derivative of fault being equal to zero required in the previous results are not needed in our work. With the support of this estimation information, a FTC scheme is well established, by which the system may recover its performance even in the occurrence of faults. Another contribution of the developed method is that all the stability criteria are deduced via fuzzy Lyapunov functions. It makes the obtained conditions more relaxed than the ones derived by quadratic Lyapunov functions. Finally, simulation results conducted on two practical dynamics are provided to show the validity of the achieved procedure.