Title :
On Iterative Learning Control of parabolic distributed parameter systems
Author :
Xu, Chao ; Arastoo, Reza ; Schuster, Eugenio
Author_Institution :
Dept. of Mech. Eng. & Mech., Lehigh Univ., Bethlehem, PA, USA
Abstract :
The iterative learning control (ILC) technique is extended to distributed parameter systems governed by parabolic partial differential equations (PDEs). ILC arises as an effective method to approach constrained optimization problems in PDE systems. We discuss both P-type and D-type ILC schemes for a distributed parameter system formulated as a general linear system Sigma(A,B,C,D) on a Hilbert space, in which the system operator A generates a strongly continuous semigroup. Under the assumption of identical initialization condition (IIC), conditions on the learning parameters are obtained to guarantee convergence of the P-type and D-type ILC schemes. Numerical simulations are presented for a 1D heat conduction control problem solved using ILC based on semigroup analysis. The numerical results show the effectiveness of the proposed ILC schemes.
Keywords :
Hilbert spaces; distributed parameter systems; iterative methods; learning systems; optimisation; parabolic equations; partial differential equations; D-type ILC scheme; Hilbert space; P-type ILC scheme; constrained optimization problem; general linear system; identical initialization condition; iterative learning control; parabolic distributed parameter system; parabolic partial differential equation; Constraint optimization; Control systems; Convergence; Distributed control; Distributed parameter systems; Hilbert space; Linear systems; Numerical simulation; Partial differential equations; Temperature control;
Conference_Titel :
Control and Automation, 2009. MED '09. 17th Mediterranean Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
978-1-4244-4684-1
Electronic_ISBN :
978-1-4244-4685-8
DOI :
10.1109/MED.2009.5164593
