Iterative learning fault-tolerant control of networked systems with quantitative sampling

For the problem of fault-tolerant control of non-linear repetitive systems with quantized error, an iterative learning fault-tolerant controller scheme with a logarithmic quantizer is constructed in this paper. Compared with the existing approaches of observer-based fault-tolerant control, the proposed iterative learning observer scheme improve the fault-tolerant control performance in the current iteration by considering the state estimation and fault estimation of the previous iteration, as well as the control error results. Meanwhile, the designed fault-tolerant controller is stable and convergent. Finally, the theoretical results are verified by numerical examples and the relationship between quantized density and controller performance is analysed.