Abstract
The event-triggered model-free adaptive control (ET-MFAC) problem for nonlinear networked control systems (NNCSs) with presence of sensor faults and denial-of-service (DoS) attacks is investigated. The attack occured in sensor-to-controller networked channels is supposed to obey the Bernoulli distribution. While sensor faults are formulated as unknown functions which could be approximated by a radial basis function-based neural networks (RBF-NNs). Then an ET-MFAC algorithm is constructed to ensure the tracking performance under sensor faults and DoS attacks based on adaptive estimations. The designed control algorithm is independent with the system structure and only uses the system input and output data. An example with comparison is given to demonstrate the validity of the new ET-MFAC algorithm.
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