Hernández-Rivera A. , VELARDE RUEDA, PABLO ANIBAL, Zafra-Cabeza A. , Maestre J.M.
No
European Control Conf., ECC
Conference Paper
Científica
01/01/2024
001290216500131
2-s2.0-85200549668
There has been significant interest in using advanced control strategies for medical treatments in recent years. This study proposes a two-fold approach to enhance drug dosing in cancer treatment. Firstly, a stochastic model predictive control (SMPC) is designed to address the uncertainties inherent in patient responses. Secondly, this SMPC is formulated as a sequential quadratic programming (SQP) MPC to manage the system's non-linearities. Therefore, this study proposes a stochastic SQP-MPC drug delivery framework to enhance patient outcomes and reduce side effects. The effectiveness of the proposed strategy is assessed via simulations and compared with other strategies. © 2024 EUCA.
Controlled drug delivery; Diseases; Model predictive control; Predictive control systems; Quadratic programming; Stochastic control systems; Stochastic models; Advanced control strategy; Cancer therapy; Drug administration; Medical treatment; Nonlinear model predictive control; Patient response; Sequential quadratic programming; Stochastic model predictive controls; Stochastics; Uncertainty; Stochastic systems