Iterative Dynamic Internal Model based ILC for a class of Nonlinear Nonaffine Discrete-time Systems

In this work, a new iterative dynamical internal model control approach (IDIMC) is presented for a nonlinear nonaffine discrete-time system with uncertainties. The CFDL-based iterative linear data model (ILDM) with one unknown parameter is used as a internal model to estimate the nonlinear process. The IDIMC consists of two parts: an iterative nominal control law designed to enable the system output track the reference trajectory perfectly, an iterative uncertainty compensation control law designed to compensate the negative effects caused by the external disturbances. The simulation study verifies the effectiveness of the proposed methods.