DocumentCode :
2789699
Title :
A design framework for Iterative Learning Control (ILC) based on 2-dimensional model predictive control (2D-MPC)
Author :
Shi, Jia ; Gao, Furong ; Jiang, Qingying ; Cao, Zikai
Author_Institution :
Dept. of Chem. & Biochem. Eng., Xiamen Univ., Xiamen, China
fYear :
2009
fDate :
17-19 June 2009
Firstpage :
1746
Lastpage :
1751
Abstract :
According to the philosophy of model predictive control (MPC), 2-dimensional (2D) MPC algorithm has been developed for the 2D system. By transforming the ILC design problem into 2D-MPC design problem, a design framework for ILC scheme, referred as 2D-MPILC, has been proposed for the repetitive processes with 2D dynamics. The major advantages of the proposed design framework is the 2D dynamics of the process and the dynamics of the cycle-varying set-point profile can be take into account in the design resulting in a time-wise feedback control and a cycle-wise high-order ILC law combined and optimized in 2D sense. The simulation results demonstrate the effectiveness and robustness of the proposed ILC scheme.
Keywords :
adaptive control; control system synthesis; feedback; iterative methods; learning systems; predictive control; 2-dimensional model predictive control; 2D dynamics; cycle-varying set-point profile dynamics; iterative learning control; repetitive processes; time-wise feedback control; Algorithm design and analysis; Chemical engineering; Chemical technology; Chemistry; Feedback control; Open loop systems; Optimal control; Prediction algorithms; Predictive control; Predictive models; 2-Dimensional (2D) system; Iterative Learning Control (ILC); Model Predictive Control (MPC);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
Type :
conf
DOI :
10.1109/CCDC.2009.5192274
Filename :
5192274
Link To Document :
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