Learning Speed Enhancement of Iterative Learning Control with Advanced Output Data based on Parameter Estimation

Gu-Min Jeong, Sang-Hoon Ji

Abstract


Learning speed enhancement is one of the most important issues in learning control. If we can improve both learning speed and tracking performance, it will be helpful to the applicability of learning control. Considering these facts, in this paper, we propose a learning speed enhancement scheme for iterative learning control with advanced output data (ADILC) based on parameter estimation. We consider linear discrete-time non-minimum phase (NMP) systems, whose model is unknown, except for the relative degree and the number of NMP zeros. In each iteration, estimates of the impulse response are obtained from input-output relationship. Then, learning gain matrix is calculated from the estimates, and by using new learning gain matrix, learning speed can be enhanced. Simulation results show that the learning speed has been enhanced by applying the proposed method.


Keywords


iterative learning control, speed enhancement, parameter estimation, learning gain estimation

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References


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DOI: http://dx.doi.org/10.15837/ijccc.2017.3.2439

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INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL (IJCCC), With Emphasis on the Integration of Three Technologies (C & C & C),  ISSN 1841-9836.

INDEXING AND COVERAGE:

***IJCCC is covered by THOMSON REUTERS and is indexed in ISI Web of Science/Knowledge Clarivate: Science Citation Index Expanded. 2016 Journal Citation Reports® Science Edition(Thomson Reuters/Clarivate, 2017): Subject Category: (1) Automation & Control Systems: Q4(2009,2011,2012,2013,2014,2015), Q3(2010, 2016); (2) Computer Science, Information Systems: Q4(2009,2010,2011,2012,2015), Q3(2013,2014, 2016). Impact Factor/3 years in JCR: 0.373(2009), 0.650 (2010), 0.438(2011); 0.441(2012), 0.694(2013), 0.746(2014), 0.627(2015). Impact Factor/5 years in JCR: 0.436(2012), 0.622(2013), 0.739(2014), 0.635(2015), 1.374(2016).

*** IJCCC is also indexed by SCOPUS (SNIP2015= 0.784): Subject Category: (1) Computational Theory and Mathematics: Q4(2009,2010,2012,2015), Q3(2011,2013,2014); (2) Computer Networks and Communications: Q4(2009), Q3(2010, 2012, 2013, 2015), Q2(2011, 2014); (3) Computer Science Applications: Q4(2009), Q3(2010, 2011, 2012, 2013, 2014, 2015). SJR: 0.178(2009), 0.339(2010), 0.369(2011), 0.292(2012), 0.378(2013), 0.420(2014), 0.319(2015). CiteScore 2016 in Scopus: 1.06.

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IJCCC is covered/indexed/abstracted in Science Citation Index Expanded (since vol.1(S),  2006). IF=1.374 in JCR2016.

IJCCC is indexed in Scopus from 2008 (SNIP2015 = 0.78, SJR2015 =0.319):

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