Blood pressure regulation by means of a neuro-fuzzy control system

A two-model multilayered neural networks (MNN) controller with modified back-propagation training algorithm is designed to adaptively control the mean arterial blood pressure. The controller is also associated with a fuzzy logic unit (LGU) to determine an incremental value and update the output weighting factor of the parallel two-model MNN controller for adequate control action. Extensive computer simulations indicate satisfactory performance and robustness of the proposed controller in the presence of much noise, over the full range of plant parameters, uncertainties and large variations of parameters.