Class Of Random System Output Feedback Control

The present paper focus on the investigation of the feedback stabilizing control for several classes of stochastic systems.The main contents of this paper are composed of the following two parts:(Ⅰ).Adaptive Output-feedback Stabilizing Control Design for Stochastic Nonlinear SystemsIn this part,we investigate the design problem of an output-feedback adaptive stabilization controller for a stochastic strict-feedback nonlinear system in observer canonical form.Comparing with previous paper,we extend the stochastic nonlinear systems to the unknown virtual control directions.Our controller design is based on the combined application of the coordinate transformation and filtered transformation techniques.In order to overcome the problem of the unknown virtual control directions,an adaptive scheme is introduced into the controller recursive design.By employing the stochastic Lyapunov-like theorem and the integrator backstepping methodology,we successfully develop an adaptive output-feedback controller which guarantees that the closed-loop system is asymptotically stable in probability.(Ⅱ).Output-feedback Stabilizing Control Design for Stochastic Nonholonomic SystemsIn this part,we consider the problem of the output-feedback control for two classes of stochastic nonholonomic systems.Firstly,eliminating the key assumption that the noise intensity is bounded,we study the output-feedback stabilization problem for a class of stochastic nonholonomic systems,where the nonlinearities depend on the unknown states of the systems.The stochastic Lyapunov-like theorem and the integrator backstepping technique are applied to the design of the controllers under the assumption that this systems with growth rate restriction.The controllers designed guarantee that the closed-loop system has an almost surely unique solution on certain time interval,the equilibrium is globally asymptotically stabilization in probability and the states can be regulated to the origin almost surely.Simulation results is addressed to illustrate the correctness of the proposed theory and approach.Secondly,we study the problem of output-feedback asymptotically stabilization problem for a class of nonholonomic systems with stochastic disturbances.The difference from the systems addressed in the first section is that in this section,the first subsystem is assumed to be linear and the nonlinearities only depend on the measurable output.Our controllers design are based on the combined application of the input/state scaling technique,the integrator bachstepping method and an observer to estimate unknown states of the systems.The controllers designed guarantee that the equilibrium is globally asymptotically stabilization in probability and can drive the system states to the origin almost surely.Besides,we give out the estimated value of unknown noise intensity.Simulation results show the effectiveness of the proposed scheme.