Adaptive control of non-affine MIMO systems with input non-linearity and unmodelled dynamics

In this study, an adaptive neural network control scheme is proposed for a class of multi-input multi-output (MIMO) non-affine systems with unmodelled dynamics and dead-zone non-linear input. This scheme solves the complexity of computation problem, broadens the variables of unmodelled dynamics and cancels the assumption of the neural network approximation error to be bounded. Using the mean value theorem and Young's inequality, only one adaptive parameter is adjusted for the whole MIMO system. By theoretical analysis, all the signals in the closed-loop systems are proved to be semi-globally uniformly ultimately boundedness. The numerical simulation illustrates the effectiveness of the proposed scheme.