I will post quotes here as I come across them:
The most important task confronting the control system analyst is developing a mathematical model of the process of interest. In many situations the essence of the analytical design problem is in the modeling: once that is done the rest of the analysis falls quickly into place.
Control System Design: An Introduction to State-Space Methods, by Bernard Friedland
This 3 minute YouTube video proposes a nice, simple five-step process:
STUDY -> MODEL -> ANALYZE -> DESIGN -> VERIFY
Credit: Jonathan Sprinkle, Aug 30, 2013
The process of designing a control system usually makes many demands of the
engineer or engineering team. These demands often emerge in a step by step design
procedure as follows:
1. Study the system (plant) to be controlled and obtain initial information about the control objectives.
2. Model the system and simplify the model, if necessary.
Multivariable Feedback Control Analysis and design by S. Skogestad and I. Postlethwaite, 2001
The construction of knowledge-driven models starts by analyzing the dominant phenomena at play, making simplifying assumptions and writing material, momentum, and/or energy balances around each part of the system under investigation.
Bonvin et al. Linking Models and Experiments, Ind. Eng. Chem. Res. 2016, 55, 6891−6903
An essential feature of control and optimisation strategies is the availability of mathematical models that accurately describe the steady-state and dynamic characteristics of the process in the whole operating range, including its non-linear behaviour.
Hodouin et al. State of the art and challenges in mineral processing control, Control Engineering Practice 9 (2001) 995–1005
From course notes for GEL-2005 Linear Systems and Control Course, U Laval, André Desbiens, 2019:
Il faut en effet bien connaître comment se comporte le procédé si on désire bien le contrôler.
Which roughly translates as:
You really need to know how the process behaves if you want to control it.