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Efficient Strategies For Robust Constrained Model Predictive Control, Marcin Tomasz Cychowski

Theses

Practical difficulties associated with the implementation of stabilizing robust model predictive control (MPC) laws are well known. The algorithms typically rely on the solution of the so-called min-max optimization problem. All such algorithms display a large online computational burden and often suffer excessive conservativeness. In this thesis, two original algorithms will be developed that address the conservativeness and complexity issues in min-max MPC.

The first algorithm is a min-max MPC based on the concept of closed-loop prediction. The synthesis procedure is realized using linear matrix inequalities and thus the implementation of the closed-loop min-max MPC control law can be performed …