1. A method of process control, comprising: representing a processing system that runs a physical process having a plurality of controlled variables (CVs) with some linear CVs and some non-linear CVs and a plurality of manipulated variables (MVs); independently developing a first linear sub-model for each of said plurality of MVs corresponding to said linear CVs a second non-linear sub-model for each of said plurality of MVs corresponding to said non-linear CVs; merging said first linear sub-model and said second non-linear sub-model to generate a first merged linear and non-linear model from dynamic process data from said processing system; repeating said independently developing and said merging to generate a second merged linear and non-linear model different from said first merged linear and non-linear model; simulating said physical process using a model predictive controller utilizing said first merged linear and non-linear model and then utilizing said second merged linear and non-linear model to obtain closed loop performance test data regarding at least one of said plurality of CVs for said first merged linear and non-linear model and for said second merged linear and non-linear model; comparing performance of said first merged linear and non-linear model with said second merged linear and non-linear model based on said closed loop performance test data, and selecting a selected process model from said first merged linear and non-linear model and said second merged linear and non-linear model.