Stable Multivariable Model Based Predictive Control
S.A. Heise and J.M. Maciejowski (submitted to the 33rd CDC)
The stability of model based predictive control (MBPC) is studied in a multiple-input, multiple-output framework in
the presence of active state and input constraints, and implemented in both an input-output and a state space format. The constrained generalized predictive control method of Rossiter and Kouvaritakis is extended to the multivariable case. In this approach, stability is established by demonstrating the existence of a monotonically decreasing cost function.
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