The Sheffield Intelligent Ventilator Advisor is a hybrid knowledge-and-model-based advisory system designed for intensive care ventilator management. It consists of a top-level fuzzy rule-based module to give the qualitative component of the advice, and a lower-level model-based module to give the quantitative component of the advice. It is structured to offer adaptive patient-specific decision support. It can be operated in either invasive or noninvasive modes depending on the availability of data from invasive clinical measurements. The user can choose between the full-advisory mode and the clinician-directed mode. The advice given by the top-level module has been validated against retrospective real patient data and compared with intensivists expertise and performance under simulation conditions. Closed-loop simulations were performed assuming various clinical scenarios including sudden changes in the patient parameters such as the shunt or deadspace with noise and disturbances. They have shown that the advice given was appropriate and the blood gases resulting from the closed-loop decision support were acceptable. The system was also shown to be tolerant to noise and disturbances. It is implemented in MATLAB/SIMULINK and LabVIEW.