Adaptive fuzzy control for pure-feedback stochastic nonlinear systems with unknown dead zone outputs

This paper focuses on an adaptive fuzzy tracking control problem for a class of pure-feedback stochastic nonlinear systems with unknown dead zone outputs. To overcome the design difficulty arising from the nonlinearity in the output mechanism, the new properties of Nussbaum function are employed and an auxiliary virtual controller is constructed. The proposed adaptive fuzzy control method guarantees that all the signals in the closed-loop system are bounded in probability and the tracking error converges to a small neighbourhood of the origin in the sense of mean quartic value. Simulation results further demonstrate the effectiveness of the presented control algorithm.