A multimodel scheduling approach is proposed for controlling strongly nonlinear processes. A global controller is built from a weighted combination of local linear controller outputs with the weights being functions of a defined closed-loop gap metric. The control algorithm is hybrid in that the global controller continuously weights the outputs of the local controllers whereas the weights are updated at constant time intervals. The proposed strategy is then implemented on two simulated processes, one of which exhibits output multiplicity and the other exhibits input multiplicity.