Practical Finite-Time Sliding Mode Control of Stochastic Systems Via Output Feedback

This paper stresses the finite-time sliding mode control (SMC) problem for a class of stochastic systems with Markov statistical properties. The control system with partial measurable system states is modeled with mismatched uncertainties. A succinct sliding variable is designed based on the measurable system states. Then, the finite-time reachability of the ideal sliding mode is analyzed and can be guaranteed by a newly designed SMC with Markov jump parameters. In the sliding mode, that the system states can converge within a finite time can be obtained by some designed solvable conditions of the controller parameters. The boundedness of the practical sliding perturbation set is subject to the mismatched uncertainties. Compared with traditional SMC, the whole convergence time of the stochastic systems can be archived within a finite time at the most, including the reaching time and the sliding time during the control process. Finally, the effectiveness of the presented control strategy is verified through a set of numerical simulation experiments.