An improved robust model predictive control approach to systems with linear fractional transformation perturbations

  • Authors:

  • Peng-Yuan Zheng;Yu-Geng Xi;De-Wei Li

  • Affiliations:

  • Department of Automation, Shanghai Jiao Tong University, Shanghai, PRC 200240 and Key Laboratory of System Control and Information Processing, Ministry of Education, Beijing, PRC;Department of Automation, Shanghai Jiao Tong University, Shanghai, PRC 200240 and Key Laboratory of System Control and Information Processing, Ministry of Education, Beijing, PRC;Department of Automation, Shanghai Jiao Tong University, Shanghai, PRC 200240 and Key Laboratory of System Control and Information Processing, Ministry of Education, Beijing, PRC

  • Venue:
  • International Journal of Automation and Computing
  • Year:
  • 2011

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Abstract

In this paper, a robust model predictive control approach is proposed for a class of uncertain systems with time-varying, linear fractional transformation perturbations. By adopting a sequence of feedback control laws instead of a single one, the control performance can be improved and the region of attraction can be enlarged compared with the existing model predictive control (MPC) approaches. Moreover, a synthesis approach of MPC is developed to achieve high performance with lower on-line computational burden. The effectiveness of the proposed approach is verified by simulation examples.