Sigurd Skogestad. Work on plantwide control

We have developed a systematic procedure for plantwide control. An important part is the selection of controlled variables based on self-optimizing control. These are the controlled variables for the "supervisory" control layer. In addition, we need a regulatory control system to stabilize the plant and avoid drift. The following paper summarizes the procedure:

S. Skogestad, ``Control structure design for complete chemical plants'', Computers and Chemical Engineering, 28 (1-2), 219-234 (2004).

There are many approaches to plantwide control as discussed in the following review paper:

T. Larsson and S. Skogestad, ``Plantwide control: A review and a new design procedure'' Modeling, Identification and Control, 21, 209-240 (2000).

There are three main layers considered in the proposed procedure:

Optimization layer (RTO; steady-state nonlinear model): Identifies activae conststraints amd computes optimal setpoints for primary controlled variables (y1).
Supervisory control (MPC; linear model with constraints): Follow setpoints for y1 (usally constant) by adjusting setpoints for secondary variables (MV=y2s)
Regulatory control (PID): Stabilizes the plant and avoids drift, in addition to following setpoints for y2. MV=valves (u).

Design starts from the bottom. A good example is bicycle riding:

Regulatory control: First you need to learn how to stabilize the bicycle
Supervisory control: Then you need to follow the road. Usually a constant setpoint policy is OK, for example, stay y1s=0.5 m from the right hand side of the road (in this case the "magic" self-optimizing variable self-optimizing variable is y1=distance to right hand side of road)
Optimization: Which road (route) should you follow?

Some more background

A chemical plant may have thousands of measurements and control loops.
By the term plantwide control is not meant the tuning and
behavior of each of these loops, but rather the formulation of
the overall control problem, and how to decompose the overall problem
into smaller blocks, that is, selection of the structure of the
control system (control structure design).

25 yeard ago Alan Foss challanged the process control research community
in his paper ``Critique of chemical process control theory'' (AIChE J., 
1973). He wrote:

   "The central issue to be resolved ... is the determination of
   control system structure.  Which variables should be measured, 
   which inputs should be manipulated and which links should be made 
   between the two sets?"

And he added

   "There is more than a suspicion that the work of a genius is needed here, 
   for without it the control configuration problem will likely remain in
   a primitive, hazily stated and wholly unmanageable form."

May be this last statement has worked as an deterrent, because there has
only been limited activity in this field over the last 25 years. Actually,
the approach to plantwide control is still very much along the lines
described by Page Buckley in his book from 1964. 

Of course, the control field has made many advances over these years, 
for example, in methods for and applications of on-line optimization 
and predictive control. Advances has also been
made in control theory and in the formulation of tools for analyzing the
controllability of a plant. These latter tools can be most helpful
in screening  alternative control structures.

Maybe the most important reason for the slow progress in plantwide
control theory is that most people do not realize that there is an
issue. But ask the question: Why are we controlling hundreds of
temperatures, pressures and compositions in a chemical plant, when
there is no specification on most of these variables? Is it just because we
can measure them or is there som deeper reason? 
The concept of  "self-optimizing control"  seems to provide the answer to
the above question.