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Iterative Learning and Fractional Reset Control

[+] Author Affiliations
S. Hassan HosseinNia

Delft University of Technology, Delft, The Netherlands

Inés Tejado, Blas M. Vinagre

University of Extremadura, Badajoz, Spain

YangQuan Chen

University of California, Merced, CA

Paper No. DETC2015-47061, pp. V009T07A041; 8 pages
doi:10.1115/DETC2015-47061
From:
  • ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 9: 2015 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications
  • Boston, Massachusetts, USA, August 2–5, 2015
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5719-9
  • Copyright © 2015 by ASME

abstract

Currently, reset control focuses on using structures with new resetting rules to avoid the occurrence of limit cycles and improve the performance of the system. A common problem in reset control is the steady-state error since it has not the same characteristic as the linear integrator, which causes the occurrence of limit cycles in many cases, specially in first order systems. It is shown that most of the reported methods to prevail this problem — resetting to non-zero values — are not robust. This paper investigates a robust solution for such phenomena using fractional order control and iterative learning control (ILC). The proposed controller is able to eliminate the limit cycle in presence of model mismatch and repetitive disturbances. Likewise, an easy way to tune is described. Simulation results are given to demonstrate its applicability and performance robustness of the designed controller is discussed.

Copyright © 2015 by ASME

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