This strategy involves a nonlinear variable transformation of a nonlinear process model. The resulting transformed process in then controlled using a linear controller and the manipulated variables for the actual process are calculated by the inverse transformations. There are several successful of this technique. However, it is critically dependent upon knowledge of the nonlinear dynamics of the processes. The nonlinear model-based control algorithms can be applied to processes described by various model equations, such as nonlinear ordinary differential equations and partial differential equations.
Model-based is a method for harnessing the power of sophisticated computer simulations in the design process with designing complex control, signal processing and communication systems. Model-based enables design engineers to evaluate the relative performance of varied control parameters in a virtual environment, (Nagy, 2004; LHP Software, 2014; Broy, 2012).