Controllability analysis for linear processes
A great amount of effort has been placed on the assessment
of controllability based on linear dynamic models.
Most controllability assessment studies based on linear models
have been concerned with the attainability of perfect
plant control, limited by factors that prevent physically realizable
inversions of the plant transfer function, such as time
delays, RHP zeros, model uncertainties, and manipulated
variable constraints.55 Two main approaches along these
lines are the dynamic resilience method, as proposed by
Grossmann and Morari56 and the functional controllability
method. These approaches for analyzing and measuring controllability
are summarized in the next two subsections.
Dynamic Resilience. The IMC controller structure presented
by Garcia and Morari57 is a powerful tool for measuring
controllability. Its assumption that the ideal controller
is the inverse of the chemical process transfer function gives
an upper bound on controllability. Dynamic resilience uses