Fuzzy adaptive output feedback control for a class of stochastic nonlinear systems under input/output quantization

In this article, a fuzzy adaptive output feedback control issue is considered for stochastic strict-feedback nonlinear system (SFNSs) under input and output quantization. In the quantized feedback control systems, to reduce the burden of communication, both the input signal and the output signal of the system are quantized, the unknown stochastic disturbances and uncertain nonlinearity are considered simultaneously. First of all, a dynamic filtering technology is applied to overcome the virtual control signals being directly differentiated. Secondly, by applying fuzzy logic systems(FLSs), the unknown nonlinear functions are approximated in the control design, a fuzzy adaptive state observer is devised for the sake of evaluating the unmeasured states. Thirdly, a novel Lemma 6 is put forward to compensate for the impact of quantization errors. Then, a novel fuzzy adaptive quantized tracking controller is established, all closed-loop signals remain bounded by the proposed controller, and the reference signal can be efficiently tracked by the actual system output. Finally, the feasibility of the presented approach is also verified by two examples.