Optimizing Control by Robustly Feasible Model Predictive Control and Application to Drinking Water Distribution Systems

  • Authors:

  • Vu Nam Tran;Mietek A. Brdys

  • Affiliations:

  • Department of Electronic, Electrical and Computer Engineering, College of Engineering and Physical Sciences., University of Birmingham, Birmingham, U.K. B15 2TT;Department of Electronic, Electrical and Computer Engineering, College of Engineering and Physical Sciences., University of Birmingham, Birmingham, U.K. B15 2TT and Department of Control Systems E ...

  • Venue:
  • ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
  • Year:
  • 2009

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Abstract

The paper consider optimizing Model Predictive Control (MPC) for nonlinear plants with output constraints under uncertainties. Although the MPC technology can handle the constraint in the model by solving constraint model based optimization task, satisfying the plant output constraints still remains a challenge. The paper proposes Robustly Feasible MPC (RFMPC), which achieves feasibility of the outputs in the controlled plant. The RFMPC is applied to control quantity which is illustrated by application to a Drinking Water Distribution Systems (DWDS) example.