Model-Free Adaptive Predictive Quantitative Control for Nonlinear Systems Subject to False Data Injection Attacks

In this paper, a model-free adaptive predictive quantitative control algorithm is presented for unknown nonlinear systems to handle the limited network transmission capacity and false data injection attacks. Firstly, a uniform quantizer with encoding-decoding mechanism is designed to deal with the network bandwidth limitation and to reduce the effects of quantization errors. Secondly, an attack compensation mechanism is conducted to reduce the impact of the false data injection attacks. Finally, simulation results show the effectiveness and robustness of the proposed control algorithm.