Abstract
Almost all existing Iterative Learning Control (ILC) algorithms have focused on One-Dimensional (1-D) dynamical systems, and seldom are used in multidimensional systems. In this article, a two-gain ILC law is presented to deal with ILC issue of Two-Dimensional (2-D) linear discrete systems described by the First Fornasini-Marchesini Model (FMMI). Convergence of the proposed ILC law under identical boundary condition is theoretically investigated. A super-vector technique is used to transfer the ILC process of 2-D FMMI into a 2-D Roessor model such that a sufficient convergence condition of the proposed ILC law is derived. Also, robustness of the proposed ILC law against iteration-variant boundary condition is illustrated by simulation.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
