Adaptive Control of Blood Pressure

Abstract
Stochastic adaptive controllers have been developed for automatic control of blood pressure during infusions of cardiostimulatory or vasoactive drugs. An adaptive algorithm based upon a minimum variance control law is presented. A more advanced algorithm obtained by augmenting the performance measure to include the rate of charge of the control signal is also presented. An autoregressive-moving-average (ARMA) model, representing the dynamics of the system, and a recursive least-squares parameter estimation technique are used for both algorithms. A series of experiments was performed in dogs, utilizing an electronically activated drug infuser. Stable control was achieved, even when the circulatory state of the animal underwent major changes, using either algorithm. On the basis of theoretical considerations and experimental results, we expect that these adaptive controllers will significantly improve the performance of drug infusion systems in clinical applications.

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