DocumentCode :
2564357
Title :
Proportional difference type iterative learning control algorithm based on parameter optimization
Author :
Hao, Xiaohong ; Owens, David ; Daley, Steve
Author_Institution :
Sch. of Electr. & Inf. Eng. Sci., Lanzhou Univ. of Technol., Lanzhou
fYear :
2008
fDate :
2-4 July 2008
Firstpage :
3136
Lastpage :
3141
Abstract :
In order to enhance learning efficiency and obtain more accuracy transient tracking performances in iterative domain, a proposition difference type operator constructed ldquofive termsrdquo parameter optimal iterative learning control algorithm based on norm performance index is proposed. The convergence condition and necessary theoretic proof is given. And the reasons why the algorithm has better learning efficiency and monotone convergence performance are discussed in detail. Finally, a class of parameter optimal iterative learning control algorithm tracking performances with different structure is compared. Simulation show that the tracking error of the proposed algorithm in this paper converges monotonically and faster than other similar algorithms.
Keywords :
adaptive control; convergence of numerical methods; iterative methods; learning systems; optimal control; optimisation; monotone convergence performance; norm performance index; parameter optimal iterative learning control algorithm; parameter optimization; proportional difference type iterative learning control algorithm; Iterative algorithms; Proportional control; Convergence Analysis; Iterative Learning Control; Parameter Optimal; Proposition Difference;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference, 2008. CCDC 2008. Chinese
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-1733-9
Electronic_ISBN :
978-1-4244-1734-6
Type :
conf
DOI :
10.1109/CCDC.2008.4597904
Filename :
4597904
Link To Document :
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