Model reference control of nonlinear MIMO systems by dynamic output feedback linearization of ANARX models

A dynamic output feedback linearization algorithm for a model reference control of nonlinear multi-input multi-output (MIMO) systems identified by an Additive Nonlinear Autoregressive eXogenous (ANARX) model is introduced. ANARX structure of the model can be obtained by training a neural network with a specific restricted connectivity structure. Linear discrete-time reference models are given in the form of a transfer matrix defining desired zeros and poles of a closed loop system. ANARX or NN-based ANARX models can be linearized by the proposed linearization algorithm in a such way that the transfer matrix of the linear closed loop system corresponds to the given matrix of the reference models.