Abstract: The present invention relates generally to methods of modeling and handling of nonlinearities for application of automatic control to systems with high inter-process variance and nonlinearities. The variance and nonlinearities make these systems difficult to control. Variance is accounted for by replacing the mathematical model of the system with a more representative model from a modelset that may or may not be chosen based on characteristics of the system under test, and then adapting using recursive estimation techniques. Nonlinearities defined by threshold to response and maximal responses are incorporated into linear models relating accumulated inputs to response. Example implementations in relation to automated drug delivery for neuromuscular blocking drugs through warning, advisory and closed-loop control systems are discussed.