Abstract
An output feedback control scheme combined with backstepping, radial basis function (RBF) neural networks, and adaptive control is proposed for the stabilization of nonlinear system with input delay and disturbances. A filter and a virtual observer are constructed to substitute the immeasurable system state. By using state transformation, the original system is converted to the system without input delay. Neural networks are employed to estimate the unknown continuous functions. The control scheme ensures that the closed-loop system is semi-globally uniformly ultimately bounded (SGUUB).
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