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.