Adaptive quantized output feedback control for nonlinear systems under deception attacks

In this paper, we consider the adaptive output feedback quantized control problem for a class of uncertain strict-feedback nonlinear systems under deception attacks. In the presence of completely unknown nonlinearities, we propose an adaptive fuzzy observer based output feedback backstepping control method. The main technical challenges lie in handling corrupted output information caused by additional attack signals and addressing reduced system stability due to input quantization. In particular, a generalized Lyapunov equation containing an unknown time-varying parameter is employed to address the output uncertainty caused by deception sensor attacks. To reduce the communication burden, a completely chattering-free logarithmic quantizer is developed, and its quantization error is handled through a decomposition technique. For the resulting closed-loop system, we show that the solutions are semi-globally uniformly ultimately bounded, and numerical simulations are carried out to verify the effectiveness of the proposed control scheme.