The design of supervisory rule‐based control in the operating theatre via an anaesthesia simulator

The development of online drug administration strategies in operating theatres represents a highly safety‐critical situation. The usefulness of different levels of simulation prior to clinical trials has been shown in previous studies in muscle relaxant anaesthesia. Thus, in earlier work on predictive self‐tuning control for muscle relaxation a dual computer real‐time simulation was undertaken, subsequent to algorithm validation via off‐line simulation. In the present approach a supervised rule‐based control algorithm is used. The control software was implemented on the actual machine to be used in theatre, while another computer acted as a real‐time patient simulator. This set‐up has further advantages of providing accurate timing and also finite data accuracy via the ADC/DAC interface, or the equivalent digital lines. Also, it provides for controller design fast simulation studies compared to the real‐time application. In this paper, a new architecture which combines several hierarchical levels for control (a Mamdani‐type fuzzy controller), adaptation (self‐organizing fuzzy logic control) and performance monitoring (fault detection, isolation and accommodation) is developed and applied to a computer real‐time simulation platform for muscle relaxant anaesthesia. Experimental results showed that the proposed algorithm fulfilled successfully the requirements for autonomy, i.e. automatic control, adaptation and supervision, and proved effective in dealing with the faults and disturbances which are normally encountered in operating theatres during surgery.