Finite-Time Stability for Non-Gaussian Stochastic Distribution Systems via T-S Fuzzy Modeling
Xiang Gu, Xiaoli Zhang, and Yang Yi
College of Information Engineering, Yangzhou University, Yangzhou, China
Abstract—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.
Index Terms—T-S fuzzy modeling, finite-time stability, probability density functions(PDFs), unknown state
Cite: Xiang Gu, Xiaoli Zhang, and Yang Yi, "Finite-Time Stability for Non-Gaussian Stochastic Distribution Systems via T-S Fuzzy Modeling," Journal of Automation and Control Engineering, Vol. 8, No. 1, pp. 9-14, June, 2020. doi: 10.18178/joace.8.1.9-14