A novel adaptive control method for a class of stochastic switched pure feedback systems.

This paper proposes a novel adaptive control approach for a class of stochastic switched nonlinear system with pure feedback structure. An important lemma is developed to overcome the design difficulty from the non-affine pure feedback structure. Combining backstepping technique with neural network approximation, a state feedback adaptive controller is given. And this controller can ensure that all of the signals in the closed-loop system are bounded, and the tracking error converges to a small enough neighborhood of the zero. A simulation example is used to verify the effectiveness of our results. [ABSTRACT FROM AUTHOR]