Data-driven fault-tolerant control for SISO nonlinear system with unknown sensor fault
Huijin Fan
National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
Search for more papers by this authorJingtian Han
National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
Search for more papers by this authorCorresponding Author
Bo Wang
National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
Correspondence Bo Wang, National Key Laboratory of Science and Technology on Multispectral Information Processing, Huazhong University of Science and Technology, Wuhan, 430074, China.
Email: [email protected]
Search for more papers by this authorHuijin Fan
National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
Search for more papers by this authorJingtian Han
National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
Search for more papers by this authorCorresponding Author
Bo Wang
National Key Laboratory of Science and Technology on Multispectral Information Processing, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China
Correspondence Bo Wang, National Key Laboratory of Science and Technology on Multispectral Information Processing, Huazhong University of Science and Technology, Wuhan, 430074, China.
Email: [email protected]
Search for more papers by this authorSummary
This paper studies the adaptive fault-tolerant control problem for a general nonlinear discrete-time SISO system with unknown system model and sensor fault. First, utilizing the input-output (I/O) data, an equivalent full-form dynamic linearization (FFDL) data model is to be constructed by introducing a pseudo-gradient vector. Then, to estimate the system's actual output from the sensor measurements corrupted by unknown faults, a nonlinear autoregressive with external input neural network (NARXNN) is employed and well-trained, by which the compensation of the fault signal can hence be derived indirectly. Based on the optimality criterion, an adaptive fault-tolerant control (FTC) strategy is therefore proposed, which promises the convergence of tracking error and the boundedness of system signals. The effectiveness of the proposed FTC algorithm is illustrated by simulation results.
CONFLICT OF INTEREST
The author declares that there is no conflict of interest.
Open Research
DATA AVAILABILITY STATEMENT
Data sharing not applicable to this article as no datasets were generated or analyzed during the current study.
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