Receding-horizon predictive control with exponential weighting

Tae Woong Yoon, David W. Clarke

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)


Exponential weighting of future tracking errors and control increments is employed for receding-horizon predictive control and seen to improve the dynamic behaviour of the closed-loop system. A sufficient condition for the asymptotic stability of generalized predictive control (GPC) with these weightings is derived. The condition can be easily satisfied whereas the corresponding condition for GPC with constant weighting is highly restrictive. In the case of constrained receding-horizon predictive control (CRHPC), a prescribed degree of stability is obtained just as with infinite-horizon optimal control using the same type of weighting. This makes it possible to use a simplified CRHPC law with no weighting on the tracking error but which guarantees convergence to the set-point faster than a bounding exponential.

Original languageEnglish
Pages (from-to)1745-1757
Number of pages13
JournalInternational Journal of Systems Science
Issue number9
Publication statusPublished - 1993 Sept
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications


Dive into the research topics of 'Receding-horizon predictive control with exponential weighting'. Together they form a unique fingerprint.

Cite this