Brief paper: On reference governor in iterative learning control for dynamic systems with input saturation

  • Authors:

  • Y. Tan;J. X. Xu;M. Norrlöf;C. Freeman

  • Affiliations:

  • The Department of Electrical and Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia;The Department of Electrical & Computer Engineering, The National University of Singapore, Singapore 117576, Singapore;Division of Automatic Control, Linköping Institute of Technology, Sweden;School of Electronics and Computer Science University of Southampton, Southampton, SO17 1BJ, United Kingdom

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2011

Quantified Score

Hi-index 22.14

Visualization

Abstract

Input saturation is inevitable in many engineering applications. Most existing iterative learning control (ILC) algorithms that can deal with input saturation require that the reference signal is realizable within the saturation bound. For engineering systems without precise models, it is hard to verify this requirement. In this note, a ''reference governor'' (RG) is introduced and is incorporated with the available ILC algorithms (primary ILC algorithms). The role of the RG is to re-design the reference signal so that the modified reference signal is realizable. Two types of the RG are proposed: one modifies the amplitude of the reference signal and the other modifies the frequency. Our main results provide design guidelines for two RGs. Moreover, a design trade-off between the convergence speed and tracking performance is also discussed. A simple simulation result verifies the effectiveness of the proposed methods.