A direct adaptive neural control for MIMO nonlinear systems with output delays

In this paper, an algorithm using an artificial neural network (ANN)-based direct adaptive control algorithm is presented for multi-input multi-output (MIMO) nonlinear systems with unknown output delays. This algorithm contains two parameter estimations, one for estimating unknown plant delays and the other for unknown control parameters. If the number of center frequency is enough, the predicted output signal can approximate the true delayed output, especially for large output delays. It is shown that the proposed algorithm not only can guarantee control parameter estimation convergence but can achieve the tracking purposes. Simulation studies are presented to validate the theoretical findings.