Brief An efficient off-line formulation of robust model predictive control using linear matrix inequalities

  • Authors:

  • Zhaoyang Wan;Mayuresh V. Kothare

  • Affiliations:

  • Chemical Process Modeling and Control Research Center, Department of Chemical Engineering, Lehigh University, Bethlehem, PA 18015, USA;Chemical Process Modeling and Control Research Center, Department of Chemical Engineering, Lehigh University, Bethlehem, PA 18015, USA

  • Venue:
  • Automatica (Journal of IFAC)
  • Year:
  • 2003

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Abstract

The practicality of model predictive control (MPC) is partially limited by its ability to solve optimization problems in real time. Moreover, on-line computational demand for synthesizing a robust MPC algorithm will likely grow significantly with the problem size. In this paper, we use the concept of an asymptotically stable invariant ellipsoid to develop a robust constrained MPC algorithm which gives a sequence of explicit control laws corresponding to a sequence of asymptotically stable invariant ellipsoids constructed off-line one within another in state space. This off-line approach can address a broad class of model uncertainty descriptions with guaranteed robust stability of the closed-loop system and substantial reduction of the on-line MPC computation. The controller design is illustrated with two examples.