The most important skill that the process engineer brings to bear on the field of process control and optimisation is his/her ability to describe the dynamics and relationships of process variables. The model (Figure 3.1) may serve several purposes:
insight and understanding;
basis for controller/optimiser design;
offline testing of controller/optimiser;
basis of filter for online estimation of process variables.
In the distant past, models sometimes ran on analogue computers – using capacitors and resistors to convert signals. However, what is being thought of here is an algorithm which will run on a digital computer. Variations to bear in mind include
theoretical versus regressed (black box);
continuous versus discrete equations;
logical versus analogue;
online versus offline;
linear versus nonlinear;
lumped versus distributed;
continuous versus discrete versus mixed inputs and outputs;
single versus multiple behaviour regimes (modes);
numerical versus analytical solution;
multi-input, multi-output (MIMO) versus single-input, single-output (SISO);
differential versus algebraic;
open loop versus closed loop;
state-space versus input–output;
deterministic versus stochastic;
approximate versus accurate;
stable versus unstable;
transfer function form versus equation form.
In this chapter, the focus will be on the modelling ...
With Safari, you learn the way you learn best. Get unlimited access to videos, live online training,
learning paths, books, interactive tutorials, and more.