Controlling the Depth of Anesthesia by Using Extended DMC

摘要

Monitoring and controlling the depth of anesthesia is really important, since over dosing and under dosing can be dangerous for the patients. Pharmacokinetic-Pharmacodynamic models vastly used for describing the relationship between input anesthetic agents and output patient endpoint variables. As there is a large variety between the patients so for controlling the depth of anesthesia we need a controller which should be robust enough and also because the anesthesia process is nonlinear and contains time delay, among them all the proposed methods for controlling the depth of anesthesia, model predictive controllers (MPCs) are good choices. Extended dynamic matrix control (EDMC) can be applied to nonlinear process control. In this method, control inputs are determined based on a linear model that approximates the process and is updated during each sampling interval. Science nonlinear relation still exists between the prediction error and the control input, numerical methods are used to solve the optimization problem defined in the method. The results showed that the performance of EDMC with or without presence of the noise and disturbance is better than GPC and also it is more robust.