HYBRID INTELLIGENT CONTROLLERS FOR A MULTIPLE DRUG DELIVERY SYSTEM IN ACUTE HEART FAILURE

Regulating the dynamic responses to multiple therapeutic agents in cases of heart failure is difficult owing to time-variant changes in drug sensitivity and interaction. To address this problem, a multiple controller based on adaptive neural network (NN) predictive control has been developed for unexpected drug responses related to cardiac output and arterial pressure. However, the control speed may be slower than that in traditional controllers because of the real-time learning process for the NN. Moreover, a proportional-integral-derivative (PID) controller alone cannot automatically update the PID parameters during drug administration. This study, therefore, aimed to make hybrid intelligent (fuzzy or NN-based PID) controllers and to evaluate the control performance during multiple drug therapy in unexpected physiological responses of heart failure. The hybrid intelligent controllers were compared with the previous PID or NN controller, and they realized robust and quick control regardless of unexpected responses and acute disruptions.

[1]  K S Narendra,et al.  IDENTIFICATION AND CONTROL OF DYNAMIC SYSTEMS USING NEURAL NETWORKS , 1990 .

[2]  J.W. Huang,et al.  Multiple-drug hemodynamic control using fuzzy decision theory , 1998, IEEE Transactions on Biomedical Engineering.

[3]  Te-Son Kuo,et al.  Adaptive control of arterial blood pressure with a learning controller based on multilayer neural networks. , 1997, IEEE transactions on bio-medical engineering.

[4]  Louis C. Sheppard,et al.  Computer control of the infusion of vasoactive drugs , 2006, Annals of Biomedical Engineering.

[5]  G. Pajunen,et al.  Model reference adaptive control with constraints for postoperative blood pressure management , 1990, IEEE Transactions on Biomedical Engineering.

[6]  Koji Kashihara Automatic Regulation of Hemodynamic Variables in Acute Heart Failure by a Multiple Adaptive Predictive Controller Based on Neural Networks , 2006, Annals of Biomedical Engineering.

[7]  R.J. Roy,et al.  Multiple drug hemodynamic control by means of a supervisory-fuzzy rule-based adaptive control system: validation on a model , 1995, IEEE Transactions on Biomedical Engineering.

[8]  G. I. Voss,et al.  Adaptive Multivarable Drug Delivery: Control of Artenal Pressure and Cardiac Output in Anesthetized Dogs , 1987, IEEE Transactions on Biomedical Engineering.

[9]  L. A. Zadeh,et al.  Making computers think like people [fuzzy set theory] , 1984, IEEE Spectrum.

[10]  R R Miller,et al.  Combined Dopamine and Nitroprusside Therapy in Congestive Heart Failure: Greater Augmentation of Cardiac Performance by Addition of Inotropic Stimulation to Afterload Reduction , 1977, Circulation.

[11]  Kumpati S. Narendra,et al.  Identification and control of dynamical systems using neural networks , 1990, IEEE Trans. Neural Networks.

[12]  D R Westenskow,et al.  Computer‐controlled Regulation of Sodium Nitroprusside Infusion , 1985, Anesthesia and analgesia.

[13]  J. G. Ziegler,et al.  Optimum Settings for Automatic Controllers , 1942, Journal of Fluids Engineering.

[14]  R.J. Roy,et al.  Hemodynamic management of congestive heart failure by means of a multiple mode rule-based control system using fuzzy logic , 2000, IEEE Transactions on Biomedical Engineering.

[15]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[16]  Lotfi A. Zadeh,et al.  MAKING COMPUTERS THINK LIKE PEOPLE , 1984 .

[17]  Koji Kashihara,et al.  Adaptive Predictive Control of Arterial Blood Pressure Based on a Neural Network During Acute Hypotension , 2004, Annals of Biomedical Engineering.

[18]  J A Blom,et al.  Automated infusion of vasoactive and inotropic drugs to control arterial and pulmonary pressures during cardiac surgery. , 1999, Critical care medicine.

[19]  James F. Martin,et al.  Multiple-Model Adaptive Control of Blood Pressure Using Sodium Nitroprusside , 1987, IEEE Transactions on Biomedical Engineering.

[20]  Ebrahim H. Mamdani,et al.  An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller , 1999, Int. J. Hum. Comput. Stud..

[21]  Koji Kashihara,et al.  Evaluation of Computer-aided Drug Delivery System with a Human Operator , 2010 .