Robust adaptive control of hypnosis during anesthesia

A closed-loop controller for hypnosis was designed and validated. The controller aims at regulating the bispectral index (BIS) with the volatile anesthetic isoflurane administered with a closed-circuit breathing system. The control algorithm consists of a cascaded internal model controller (IMC) where the master loop aims at regulating BIS. The slave loop tracks endtidal concentration references provided by the master controller. In the paper, a tuning method is presented. First, a robust design procedure which guarantees stability of the slave controller despite parametric uncertainties is described. Then, we demonstrate how the estimation of the drug´s equilibration constant k_e0 greatly improves performance if the estimated value is used to update the models in the control scheme. In order to do so, an identification scheme for k_e0 is proposed, which requires estimation of the drug´s time to peak effect t_peak. The identification algorithm requires few modeling assumptions and guarantees convergence. Simulation results are presented, which quantify both the performance of the identification scheme and the improvement of the closed-loop control performance.