Title :
Iterative Learning Control for 2-D linear discrete systems with Roessor´s model
Author :
Fan Wu ; Xiao-Dong Li
Author_Institution :
Sch. of Inf. Sci. & Technol., Sun Yat-sen Univ., Guangzhou, China
Abstract :
Almost all existing Iterative Learning Control (ILC) methods are specifically designed for the one-dimensional dynamical systems. And many two-dimensional dynamical systems are often required to do repeatable works in engineering fields. This paper presents a novel P-type ILC rule for the two-dimensional systems represented by Roessor´s model. The proof on convergence of the proposed ILC rule is based on the solution formula of the two-dimensional Roessor´s model in ILC process. By transferring the ILC tracking errors into a one-dimensional system in iteration direction, the convergence condition of the proposed ILC rule is derived.
Keywords :
discrete systems; iterative methods; linear systems; neurocontrollers; 2D linear discrete systems; ILC methods; P-type ILC rule; Roessor model; iterative learning control; Convergence; Eigenvalues and eigenfunctions; Iterative methods; Manipulators; Process control; Vectors; 2-D linear discrete systems; Iterative learning control; Roessor´s model;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-1-4673-1871-6
Electronic_ISBN :
978-1-4673-1870-9
DOI :
10.1109/ICARCV.2012.6485203