Fault-tolerant design of non-linear iterative learning control using neural networks - Patan, Krzysztof; Patan, Maciej (1975- )
The design of neural-network-based iterative learning control for non-linear systems is addressed in the setting of a fault tolerant control regime. Taking advantage of the repetitive character of the control task, the inherent uncertainty related to a potential faulty system state can be properly accommodated in terms of a data-driven iterative learning scheme with neural networks used for forward/inverse modeling as well as for controller synthesis.
Keywords: iterative learning control; convergence; neural networks; fault tolerance; fault accommodation