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Stability proof for computationally efficient predictive control in the uncertain case

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3 Author(s)
J. A. Rossiter ; Dept. Autom. Control & Syst. Eng., Univ. of Sheffield, UK ; B. Kouvaritakis ; M. Cannon

Large system dimensions and/or a possible need for long horizons restrict the applicability of predictive control. Earlier work showed that by sacrificing a certain degree of optimality it is possible to define efficient algorithms which reduce considerably computational complexity. This note considers a class of such algorithms which deploy just one degree of freedom. It is shown that it is possible to: (1) derive a priori stability guarantees over much larger regions of the state space and for a larger class of control trajectories; (2) account for a particular class of model uncertainty; and (3) show that even though a use is made of ellipsoidal invariant sets, nevertheless the stability results are not limited to the volume of such ellipsoids.

Published in:

American Control Conference, 2003. Proceedings of the 2003  (Volume:3 )

Date of Conference:

4-6 June 2003