Adaptive control of closed-circuit anesthesia.

Closed-circuit anesthesia (CCA) is more economical and ecologically safer than open circuit anesthesia. However, gas concentrations are more difficult to control. Computer control of CCA has been proposed to facilitate its use. Past efforts have either been limited to the control of anesthetic gas concentrations or apply only to a small group of patients. This paper describes a comprehensive control system applicable to a large class of patients. This system controls the end-tidal oxygen and anesthetic gas concentrations, and the circuit volume. The CCA process was modeled by writing mass balance equations. Simplifying assumptions yielded a bilinear single-input-single-output model for the anesthetic gas concentration and a bilinear multiple-input-multiple-output model for the circuit volume and oxygen concentration. One-step-ahead controllers were used to control these two subsystems. Simulations showed that the control performance was most sensitive to the gas uptakes. Three independent, least-mean-squares estimation schemes were implemented to estimate the uptakes of oxygen, nitrous oxide, and anesthetic gas. These estimates were used in the control law and resulted in explicit adaptive control. The performance of the adaptive controller was compared to that of a fixed controller (with precalculated gas uptakes) in five animal experiments. The adaptive controller performed better than the fixed controller in all cases. The most significant difference was in the anesthetic gas response time 3.6 +/- 0.70 min for adaptive control and 7.04 +/- 5.62 min for fixed control. The adaptive controller was also robust with respect to variations in the system parameters such as the functional residual capacity, leak, deadspace and gas uptakes.(ABSTRACT TRUNCATED AT 250 WORDS)