Adaptive output tracking of unknown MIMO nonlinear systems using radial basis function neural networks

摘要

In this paper, a neural-network-based adaptive control is presented to solve the output tracking problem for a class of nonlinear continuous-time feedback linearizable MIMO systems with unknown nonlinearities. The adaptive control adopted in this paper ingeniously combines the conventional sliding control technique and the approxi- mation scheme of the radial basis function(RBF) neural networks to perform approx- imating input-output linearization.