Direct adaptive control for a class of multi-input and multi-output nonlinear systems using neural networks

In this paper, direct adaptive neural network control is studied for a class of multi-input and multi-output (MIMO) nonlinear systems based on input-output model with unknown inter connections between subsystems. The proposed adaptive algorithm is very simple and easy to implement. By finding a unitary orthogonal matrix to tune the NN weights, the closed-loop system is proved to be semi-globally uniformly ultimately bounded (SGUUB). The control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.