Supervised multi-model adaptive control of neuromuscular blockade with off-set compensation

The paper considers the control of neuromuscular blockade (NMB) induced by atracurium on patients subject to general surgery. The high levels of uncertainty in the process model are tackled with supervised multi-model adaptive control, for which an innovative supervisor based on least squares estimation is presented to deal with constant unknown offsets in output measurement. In order to avoid excessive switching among the controllers, a model clustering is made, with a common controller in each cluster. Furthermore, an anti-windup algorithm that may be applied to an integrator that is common to a bank of controllers is proposed. The control structure is tested on simulation using realistic nonlinear models for NMB with parameters estimated from actual patient data.