Monitoring and control of physiological variables during surgeries is a difficult task since the manual infusion of drugs leads to complications in patients. Anaesthesia is mainly used to maintain most the critical physiological parameters. Automatic control of these para meters will help the anaesthetist to focus on other issues that has to be taken care of. This paper presents about the closed loop control of anaesthesia drug that is used to maintain the safety limits of physiological variables such as hypnosis in terms of Bi-Spectral Index (BIS), analgesia in terms of Mean Arterial Pressure (MAP) and Heart Rate (HR). Here isoflurane is anaesthesia that is used as the medicine to administer the parameters. Pharma cokinetic (PK) and Pharmacodynamic (PD) modeling is carried out for isoflurane drug and control action is implemented based on the open loop response of the PK-PD model. The performance of the model is compared for Proportional-Integral (PI) controller and Neural Network Internal Model Control (NN-IMC) and the simulation results are obtained using MATLAB.

Baroreceptor is the feedback unit present in the living beings which acts as a sensor that is located in the walls of blood vessels. This sensor senses the deformation in the blood vessels which causes change in arterial blood pressure and regulates it via Central Nervous System (CNS) and the information are autonomic reflexes that has a great influence on circulatory system elements such as peripheral systemic resistance (Rpsym), contractility of the ventricles (Emax), unstressed volume of the ventricles (Vus_ven) and heart rate (HR). The dynamic behaviour of the baroreceptor is modeled and substantiated by applying the negative feedback mechanism. A detailed modeling and simulation study is presented considering various testing conditions in regulating the circulatory system elements which oversees the Mean Arterial Pressure (MAP) in cardiovascular system. The Total Artificial Cardiovascular model (TAH-CVS) is also developed using pressure, volume and flow related differential equations. Based on the testing conducted under various conditions, the feedback-mechanism of the baroreceptor model is combined with the continuous TAH-CVS closed loop model to validate the effectiveness of the baroreceptor model. The simulation results of TAH-CVS model at initial conditions are compared with the TAH-CVS model with baroreceptor.