RHONN identifier for unknown nonlinear discrete-time delay systems

This work proposes a discrete-time nonlinear neural identifier based on a Recurrent High Order Neural Network (RHONN) trained with an Extended Kalman Filter (EKF) based algorithm for discrete-time deterministic multiple input multiple output (MIMO) systems with unknown dynamics and time-delay. Applicability of the proposed identifier is shown via experimental results performed under the presence of unknown external and internal disturbances as well as unknown time-delays.