Adaptive Quantized Controller Design Via Backstepping and Stochastic Small-Gain Approach


This paper addresses an output feedback stabilization problem for a class of stochastic nonlinear systems with unmodeled dynamics preceded by hysteretic quantized input. To deal with unmeasurable states, a completely unique state observer that contains the quantized management is introduced. By presenting a brand new nonlinear decomposition for the hysteretic quantized input, the major technique problem coming from the discrete quantized input is overcome. By utilizing the backstepping technique and using the stochastic little-gain theorem, an on the spot adaptive fuzzy output feedback management theme is developed. The proposed style approach will guarantee that the closed-loop system is input-to-state practically stable in probability. Finally, a simulation example verifies the proposed control theme.

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