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Robustness and load disturbance conditions for state based iterative learning control
Author(s) -
Alsubaie Muhammad A.,
Rogers Eric
Publication year - 2018
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2460
Subject(s) - iterative learning control , control theory (sociology) , robustness (evolution) , computer science , disturbance (geology) , transfer function , convergence (economics) , representation (politics) , control engineering , repetitive control , robust control , control system , control (management) , engineering , artificial intelligence , biochemistry , chemistry , biology , economic growth , politics , law , political science , electrical engineering , economics , gene , paleontology
Summary Robust conditions and load disturbance limitations are developed for the design of iterative learning control laws for linear dynamics for two commonly used schemes. Many industrial applications encounter periodic disturbances acting on the input of a system operating under repetitive control, which can be represented by a time delay model whose output is applied to the system input in the mathematical representation of the controlled dynamics. The design isolates the disturbance system and defines the overall transfer function around the delay model. Then, the small gain theorem can be used to develop conditions for disturbance accommodation and error convergence of the repetitive control scheme. A simulation case study to support the new results is given, where the model used has been developed by frequency response tests on a gantry robot and is a necessary step before experimental verification.