Explicit hybrid model predictive control strategies for intravenous anaesthesia

- A nominal hybrid explicit/multiparametric MPC structure was developed based on a piece-wise affine approximation of the intravenous anaesthesia model, which efficiently addresses the nonlinearity of the Hill curve.
- Simultaneous hybrid mp-MPC and multiparametric moving horizon strategy was developed and implemented for the intravenous anaesthesia process.
- Robust hybrid mp-MPC strategies were developed and simultaneously implemented and tested for the intravenous anaesthesia process.
- The developed strategies successfully address two of the main challenges in the control of the intravenous depth of anaesthesia: nonlinearity and inter-and intra- patient variability.

In this work, we first present a piece-wise affine model for intravenous anaesthesia, based on which a hybrid explicit/multiparametric model predictive control strategy is developed. To deal with the inter- and intra-patient variability, an estimation strategy, the multiparametric moving horizon estimator, and different robust algorithms such as Offset Correction, State-Output Correction and Prediction Output Correction are further designed and implemented simultaneously with the hybrid multiparametric model predictive control. Simulation results for a set of 12 virtually generated patients for the regulation of the depth of anaesthesia by means of the Bispectral Index with Propofol as the anaesthetic, demonstrate the validity and usefulness of the proposed advanced control and estimation strategies.