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Finite-Time Stability for Non-Gaussian Stochastic Distribution Systems via T-S Fuzzy Modeling

In this paper, the problem of finite-time stability for general non-Gaussian stochastic system with unknown state is investigated by using T-S fuzzy modeling. The objective is to control the probability density functions(PDFs) of the system output to follow a given PDFs. In order to describe the gray-box dynamics between PDFs of system output and controlled input, the well known fuzzy logic systems and the T-S fuzzy models are imported at the same time. Then a classical state observer is used to imitate the unknown state of the system. On account of the strong nonlinearity stochastic process, the square root B-spline is used to model the target PDFs. Finally, the favorable finite time stability can be achieved by employing convex optimization theory. Simulations study for a non-gaussian model are given to embody the superiority of the designed algorithm. 