Abstract
An adaptive control scheme combined with backstepping, radial basis function (RBF) neural networks is proposed for the output tracking control problem of a class of MIMO nonlinear systems with input delay and disturbances. 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). The tracking error is proved to be bounded and ultimately converges to an adequately small compact set. The feasibility is investigated by a simulation example.
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