Title :
Blood pressure regulation by means of a neuro-fuzzy control system
Author :
Chen, Chin-Te ; Lin, Win-Li ; Kuo, Te-Sou ; Wang, Cheng-Yi
Author_Institution :
Dept. of Electr. Eng., Taiwan Univ., Taiwan
fDate :
31 Oct-3 Nov 1996
Abstract :
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
Keywords :
adaptive control; digital simulation; fuzzy control; fuzzy neural nets; haemodynamics; neurocontrollers; patient treatment; pressure control; blood pressure regulation; computer simulations; incremental value; mean arterial blood pressure; modified back-propagation training algorithm; neuro-fuzzy control system; output weighting factor; parameter variations; plant parameters; sodium nitroprusside drug; two-model multilayered neural networks controller; uncertainties; Algorithm design and analysis; Arterial blood pressure; Blood pressure; Computer simulation; Control systems; Fuzzy logic; Multi-layer neural network; Neural networks; Noise robustness; Pressure control;
Conference_Titel :
Engineering in Medicine and Biology Society, 1996. Bridging Disciplines for Biomedicine. Proceedings of the 18th Annual International Conference of the IEEE
Conference_Location :
Amsterdam
Print_ISBN :
0-7803-3811-1
DOI :
10.1109/IEMBS.1996.647632
