Output Information Based Iterative Learning Control Law Design With Experimental Verification
2012 ◽
Vol 134
(2)
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Keyword(s):
This paper considers iterative learning control law design using the theory of linear repetitive processes. This setting enables trial-to-trial error convergence and along-the-trial performance to be considered simultaneously in the design. It is also shown that this design extends naturally to include robustness to unmodeled plant dynamics. The results from experimental application of these laws to a gantry robot performing a pick and place operation are given, together with a discussion of the positioning of this approach relative to alternatives and possible further research.
2020 ◽
Vol 95
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pp. 104260
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Keyword(s):
2018 ◽
Vol 2018
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pp. 1-15
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Keyword(s):
2018 ◽
pp. 251-259
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2020 ◽
Vol 234
(7)
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pp. 792-808
Keyword(s):
2017 ◽
2016 ◽
Vol 40
(1)
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pp. 49-60
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Keyword(s):