1. A method for training a steady-state non-linear model of a plant, comprising the steps of: generating an input set of historical training data representative of the historical operation of the plant and having input data u(t) and output data y(t); identifying a linear dynamic model of the plant representing the dynamics of the plant for a given output variable of the plant; pre-filtering the historical input data through the dynamic model to impress the dynamics of the plant as defined by the linear dynamic model on the input data u(t); and training a non-linear model of the plant with the pre-filtered input data u(t) to provide a stored representation of the steady-state operation in the non-linear model associated with the given output variable.