Output-feedback Control For Stochastic Nonlinear Systems With Unknown Sensor Sensitivity

Research on the control design of stochastic nonlinear systems has attracted much attention due to their wide practical applications.Based on stochastic nonlinear systems theory,most of existing literature assumes that system is free of sensor sensitivity error or the relationship between the output and the state is explicitly clear.In the fact,due to manufacturing reasons,there always exists a sensitivity error where the sensor sensitivity is neither known nor differentiable.And the existence of stochastic noise makes the research in this paper more involved and difficult.In this paper,we study a class of the output-feedback control for stochastic feedforward nonlinear systems with Markovian switching and unknown measurement sensitivity,and a class of stochastic strict-feedback systems with sensor uncertainty and unknown growth rate.This paper is composed of the following two parts.Firstly,consider the problem of output-feedback control for stochastic feedforwa--rd nonlinear systems with Markovian switching and unknown measurement sensitivity.By developing a state observer and an output feedback control law,it is shown that the closed-loop system has a unique solution and the solution of the closed-loop systems is almost surely asymptotically stable.Secondly,consider the problem of output-feedback control for stochastic strict-feedback systems with sensor uncertainty and unknown growth rate.By developing a dual-domination approach,an adaptive observer and an output-feedback controller are designed.By using the nonnegative semimartingale convergence theorem,it is proved that the closed-loop system has an almost surely unique solution on [0,(10)?(8)and the solution of the closed-loop systems is almost surely asymptotically stable.