This thesis aim is to purpose the design of an automatic close-loop control system for general anaesthesia. General anaesthesia is achieved through the administration of pharmaceutical drugs, which produce an effect on patients undergoing surgery. To achieve the aim of this research clinical data obtained from a setup assembled at King's College Hospital and used for estimation and optimization of Pharmacodynamic (PD) models associating effect-site concentrations of propofol, remifentanil and cardiac output to BIS readings. These models were estimated using two techniques, Hill equation and support vector regressors (SVRs) based models. The use of SVRs as a modelling technique allows the incorporation of additional biological signals The SVR technique may produce a nonparametric model which does not guarantee total adequacy of the estimated model as a PD model, therefore a Model Adequacy Index was proposed to assess compliance of the estimated models based on the expected clinical behaviour. PD models considering both pharmaceutical drugs estimated through the SVR technique and Gaussian radial basis kernel presents a considerably higher performance when compared to the estimated multidrug Hill model. Three proportional-integral-differential (PID) controllers are employed, namely linear PID controller, type-1 (T1) fuzzy PID controller and interval type-2 (IT2) fuzzy PID controller, to regulate the bispectral index using the nominal patient's model. The PID gains and membership functions are obtained using genetic algorithm (GA) by minimizing a cost function measuring the control performance. The best trained PID controllers are tested under different scenarios and compared in terms of control performance. Simulation results show that the IT2 fuzzy PID controller offers the best control strategy regulating the BIS index while the T1 fuzzy PID controller comes second.