Abstract
In this work, different control laws of Model Predictive Control (MPC) are offered in order to improve the stability and robustness aspects. The CRHPC (Constrained Receding-Horizon Predictive Control) provides de stability (in the absence of uncertainty), and the BDU (Bounded Data Uncertainties) technique provides a guided regularization improving the robustness and ill-conditioning, presenting the original CRHPC-BDU. The objective of this work consists, on the one hand, of offering alternative control laws of the CRHPC, using different mathematical tools and comparing them. These ones constitute the basis for the different statements for extending these strategies to the CRHPC-BDU. So, one of the main contribution consists of obtaining a more robust and with less computationalcost version of CRHPC-BDU.
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