Adaptive output feedback control of stochastic systems with mismatched uncertainties input-output quantization

Inspired by the fact that remote control systems always demand to be quantified, and considering that there are always stochastic disturbances in the actual situation, this study discusses a sort of systems with unknown constants due to the existence of parameters that are untoward to measure. Therefore, in this research, a sort of stochastic nonlinear systems with input-output quantization mismatched uncertainties is studied by utilizing backstepping method. The difficulty is that the output signal becomes non-differential after being quantized. In addition, only the quantized output signal in the system can be regarded as known during the analysis. Therefore, the update of unknown parameters and the design of controller will grow arduous. In order to solve the above dilemma, a state observer and a projection operator are introduced. Moreover, in the design of the controller, the power form of Lyapunov function and differential method is employed to avoid the derivation of non-differentiable functions. Since the controller proposed in this study contains a small number of parameters that need to be designed, it is practical and can eliminate the problem of computational explosion. Simulation results demonstrate the effectiveness of the proposed scheme.