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Online Identification and Internal Model Control for Regulating Hemodynamic Variables in Congestive Heart Failure Patient

Arpita Bhattacharjee and Ashoke Sutradhar
Electrical Engineering Department, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, India

Abstract—This paper deals with one of the most challenging task of simultaneous control of two hemodynamic variables by the infusion of sensitive cardiac drugs in congestive heart failure (CHF) patients. A nonparametric internal model control (IMC) algorithm along with an integral control action has been proposed in this work for regulating two hemodynamic variables, the mean arterial pressure (MAP) and the cardiac output (CO) by simultaneous administration of two drugs – sodium nitroprusside (SNP) and dopamine (DPM). The two-input two-output physiological model of CHF patient is identified online by solving Volterra kernels from the input-output data of the physiological process. FFTs are taken on respective time domain kernels to obtain the Volterra transfer function (VTF) of the multivariable system. The internal model control algorithm is developed using this VTF. The integral control action has been combined with IMC for set-point tracking. Using this closed loop control algorithm MAP and CO reaches the steady state value within a very short time with the minimum infusion of highly sensitive cardiac drugs in presence of actuator and sensor noises.

Index Terms—online identification, nonparametric model, Volterra kernel, internal model control, congestive heart failure.

Cite: Arpita Bhattacharjee and Ashoke Sutradhar, " Online Identification and Internal Model Control for Regulating Hemodynamic Variables in Congestive Heart Failure Patient," International Journal of Pharma Medicine and Biological Sciences, Vol. 4, No. 2, pp. 85-89, April 2015. doi: 10.18178/ijpmbs.4.2.85-89
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