The model-based control design process involves modeling the plant to be controlled, analyzing and synthesizing a controller for the plant, simulating the plant and controller, and deploying the controller.
For control design engineers, National Instruments provides a powerful set of mathematical algorithms, in the MATRIXx and LabVIEW System Identification tools, that reduce the effort required to develop models for model-based design. Unlike modeling from first principles, which requires an in-depth knowledge of the system under consideration, system identification methods can handle a wide range of system dynamics without knowledge of the actual system physics.
Choosing a suitable model structure is prerequisite before its estimation. The choice of model structure is based upon understanding of the physical systems. Three types of models are common in system identification: the black-box model, grey-box model, and user-defined model. The black-box model assumes that systems are unknown and all model parameters are adjustable without considering the physical background. You cannot adjust all the parameters arbitrarily. The grey-box model assumes that part of the information about the underlying dynamics or some of the physical parameters are known and the model parameters might have some constraints. The user-define model assumes that commonly used parametric models cannot represent the model you want to estimate. You can define your special system model by using a template VI with a predefined input-output interface.