Adaptive fuzzy decentralised output feedback control of pure-feedback large-scale stochastic non-linear systems with unknown dead zone

In this study, a robust adaptive fuzzy decentralised backstepping output feedback control approach is proposed for a class of uncertain non-linear stochastic large-scale systems in pure-feedback form. The non-linear large-scale systems under study have unknown non-linear functions, unknown dead-zone and immeasurable states. Fuzzy logic systems are used to approximate the unknown non-linear functions, and a K-filters state observer is designed for estimating the unmeasured states. Based on the information of the bounds of the dead-zone slopes as well as treating the time-varying inputs coefficients as a system uncertainty, a robust adaptive fuzzy decentralised output feedback control approach is constructed via the backstepping recursive design technique. It is shown that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are semi-globally uniformly ultimately bounded in probability, and the observer errors and the output of the system can be regulated to a small neighbourhood of the origin by choosing design parameters appropriately. A simulation example is provided to show the effectiveness of the proposed approach.