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Direct Adaptive Fuzzy Backstepping Control for Stochastic Nonlinear SISO Systems with Unmodeled Dynamics
Author(s) -
Zhang Xiumei,
Liu Xikui,
Li Yan
Publication year - 2018
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1615
Subject(s) - backstepping , control theory (sociology) , nonlinear system , fuzzy logic , computer science , stability (learning theory) , fuzzy control system , scheme (mathematics) , control (management) , adaptive control , control engineering , mathematics , engineering , artificial intelligence , mathematical analysis , physics , quantum mechanics , machine learning
This paper discusses the input‐to‐state practical stability (ISpS) problem for a class of stochastic strict‐feedback systems which possess dynamic disturbances, unstructured uncertainties and unmodeled dynamics. The uncertain terms not only depend on the measurable output, but also are related with other unmeasurable states of the system. In the backstepping design, we use fuzzy logic systems directly to approach unknown control signals rather than unknown functions. A main advantage of the direct control method is that for an n th order strict‐feedback stochastic system, only four online parameters are needed. Moreover, it is proved that the closed‐loop system is ISpS in probability by using a stochastic small‐gain approach. Two simulation examples illustrate the effectiveness of the proposed scheme.