Nonlinear adaptive control of the NeuroMuscular Blockade in anesthesia

This paper presents a nonlinear adaptive control strategy based on the Wiener model for control of the Neuro-Muscular Blockade in anesthesia. The structure combines the inversion of the static nonlinearity present in the Wiener model with a pole-placement controller for the linearized system. The overall strategy exploits identification of a minimally parameterized model for the description of the effect of the muscle relaxant atracurium in the NeuroMuscular Blockade. An Extended Kalman Filter was developed for that purpose, providing estimates of the model parameters for both the linear controller and the blocks where the inversion of the static linearity is performed. Simulations were run in a database of 100 patients simulated with the standard physiologically-based pharmacokinetic/pharmacodynamic model for the NeuroMuscular Blockade. The results show that the nonlinear adaptive controller performs well regarding reference following and tackles changes in the patient´s dynamics. Noisy scenarios were also simulated to test the robustness of the proposed strategy.