Neural network-based sliding mode control for a class of uncertain systems with measurement noise

In this paper, we consider sliding mode control (SMC) of uncertain systems whose output is contaminated by external disturbances. The cone-bounded assumption on uncertainties is removed via neural networks. The proposed sliding-mode controller can not only guarantee a uniform ultimate boundedness of states of the plant, but also the boundedness of all other signals in the closed-loop system.