Dynamic ILC for Linear Repetitive Processes Based on Different Relative Degrees

The current research on iterative learning control focuses the condition where system relative degree is equal to 1, while 0 or greater than 1 not considered. Therefore, this paper studies monotonic convergence of corresponding dynamic controller systematically for discrete linear repetitive processes with different degrees. First, a 2D Roesser model presented by means systems theory. Then, controlled analyzed according stability theory process. Furthermore, sufficient conditions existence are given in matrix inequality format under degrees, which guarantees performance. Finally, through comparison static controllers simulation results show that designed schemes effective and feasible.