Output feedback domain stabilization in probability in fixed time for nonlinear stochastic systems. Issue 18 (December 2021) - Yin, Juliang
Abstract: This work is concerned with the domain stabilization in probability in fixed time for stochastic nonlinear systems with outputs. The purpose of stabilization is to find a suitable output feedback controller such that the trajectory of the resulting closed-loop stochastic system, starting from an initial value outside a given target domain D, could arrive at the target domain in fixed time T with a minimum probability p . A separation result is shown under Lyapunov-based assumptions, which decomposes the control design into a state feedback problem and a filtering problem. Accordingly, the design of the output feedback controller is proposed with the help of the separation result under certain conditions. Furthermore, design procedures are given to accomplish the purpose of domain stabilization in probability in fixed time for a class of nonlinear stochastic systems. The ARE-based method is applied to solve the state feedback problem, whereas high-gain observers and saturation control techniques are used for the filtering problem. An example is provided for demonstration.