Decentralized iterative learning control for large-scale interconnected linear systems with fixed initial shifts

  • Qin Fu
  • Pan-Pan Gu
  • Jian-Rong Wu
Regular Papers Control Theory and Applications


This paper deals with the problem of iterative learning control for large-scale interconnected linear systems in the presence of fixed initial shifts. According to the characteristics of the systems, iterative learning control laws are proposed for such large-scale interconnected linear systems based on the PD-type learning schemes. The proposed controller of each subsystem only relies on local output variables without any information exchanges with other subsystems. Using the contraction mapping method, we show that the schemes can guarantee the output of the system converges uniformly to the corresponding output limiting trajectory over the whole time interval along the iteration axis. Simulation examples illustrate the effectiveness of the proposed method.


Decentralized control fixed initial shifts iterative learning control large-scale interconnected linear systems PD-type learning schemes 


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Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.School of Mathematics and PhysicsSuzhou University of Science and TechnologySuzhouP. R. China

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