Abstract
The output feedback controller is designed for a class of stochastic nonlinear systems that satisfy uncertain function growth conditions for the first time. The multivariate function growth condition has greatly relaxed the restrictions on the drift and diffusion terms in the original stochastic nonlinear system. Here, we cleverly handle the problem of uncertain functions in the scaling process through the function maxima theory so that the Ito differential system can achieve output stabilization through Lyapunov function design and the solution of stochastic nonlinear system objects satisfies the existence of uniqueness, ensuring that the system is globally asymptotically stable in the sense of probability. Furthermore, it is concluded that the system is inversely optimally stable in the sense of probability. Finally, we apply the theoretical results to the practical subsea intelligent electroexecution robot control system and obtain good results.
Highlights
In the field of control theory, research on the output feedback control of stochastic nonlinear systems has produced some valuable results
Krsticand Kanellakopoulos [11] studied the design of output feedback controllers for a class of stochastic nonlinear systems (1). e nonlinear terms in this system are all functions that can measure the output for the first time
In [37], a state observer is constructed by introducing coordinate transformation, and the Lyapunov function is selected to study the design of output feedback controllers for stochastic nonlinear systems in a more general condition
Summary
In the field of control theory, research on the output feedback control of stochastic nonlinear systems has produced some valuable results. E authors used the coordinate transformation method in nonlinear theory to construct a state observer for a stochastic nonlinear system, selected an appropriate Lyapunov function, and designed an output feedback controller which satisfies the system’s stabilization conditions. In [37], a state observer is constructed by introducing coordinate transformation, and the Lyapunov function is selected to study the design of output feedback controllers for stochastic nonlinear systems in a more general condition. Is paper focuses on the output feedback problem of a class of stochastic nonlinear systems that satisfy the growth conditions of the form of an uncertain function. By setting a series of Lyapunov functions and using the backstepping method, authors can get an output feedback controller with high-gain parameters so that the solution of the random nonlinear system object satisfies the existence of uniqueness while ensuring that the system is globally asymptotically stable in probability. In the last step through backstepping theory, select the ux[n] − Kn p 1 ( x ) + · · · + p n ( x ) vnwθn
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