Sigurd Skogestad. Research.

The objcetive of our research is to develop simple yet rigorous methods to solve problems of engineering significance. We would like to provide the engineer with tools to assist in problem solving.

Main research areas:

Use of feedback

The use of feedback is an important theme in many parts of our research. Most chemical engineeers are (indirectly) trained to be ``feedforward thinkers'' and they immediately think of ``model inversion'' when it comes doing control. Thus, they prefer to rely on models instead of data, although simple feedback solutions in many cases are much simpler:
  1. Feedback solutions are less sensitive to uncertainty and disturbances.
  2. Feedback is the only way of changing the dynamics of a system.
  3. Feedback can be used without any model if applied locally such that high-gain feedback can be used.
  4. Feedback applied locally may remove nonlinearity.
An interesting aspect is the use of feedback hierarchies based on local feedback loops which operate independently (in parallel). As everyone knows there are used extensively in practice - in a chemical plant there may be 3 or 4 layers - but there seems to be little theory (see again Chapter 10 in my book for some initial attempts). By closing a feedback loop, the number of independent variables remains the same (the setpoint becomes the new one), but the price we have to pay for using the local feedback loop is that it uses up some part (the fastest) of the dynamic range. A rule of thumb is that the time scales for the layers must be separated by at least a factor 10; e.g. we may have that layer 1 (the lowest) operates within a time scale of 10 s, layer 2 within 100 s, layer 2 within 1000 s, etc. The idea is that the time scale separation should be such that we need not worry about the dynamics of the level below works - we should be able to assume that when we change the independent variable (a setpoint to the layer below) then it changes ``immediately'' (within the time scale of present interest). In conclusion, an important reason for use feedback hierachies, is to avoid the need for having a large model with all the dynamics included; at each level one only needs to have a model which covers the local variables and their dynamics at the time scale of the local loop (if the dynamics are dominantly first order; then simple P-control with needs essentially no model may be used).

We are also looking into how feedback can be best utilized for online optimization. A key is to find the appropriate feedback variable -- see also Chapter 10 in my book for more details. For example, we have applied temperature control feedback to get a an indirect level control which then provides a simple and workable scheme for multivessel batch distillation.

Another somewhat indirect way of utilizing feedback, is to use the measurements to update parameters and states in a model. We want to compare this approach with the more ``direct'' approach of local feedback loops. The goal is to find the right balance between this ``indirect'' (using models) use of feedback and the ``direct'' approach (using data, i.e. measurements) with local feedback.

-Sigurd Skogestad (Aug./Sept. 1997)

Plantwide control and "self-optimizing control"

(This is very much related to the above feedback ideas) 
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, and we are working on this idea, including on
providing some good examples.

(Sigurd Skogestad, March 1998)
Jan. 2002:
More generally, the following definition of self-optimizing control is probably useful.

"Self-optimizing control is when acceptable operation under all conditions is achieved with constant setpoints for the controlled variables."

Here "acceptable operation" is more precisely defined by the value of the loss, and "under all conditions" means for the defined disturbances, plant changes and implementation errors.

To include biological system the term "self-optimizing control" should possibly be broadened further, for example, by replacing "with constant setpoints for the controlled variables" by "by controlling the right variables" or something similar.

References:

More

Some old research projects

  1. EU Joule project: Complex distillation columns (DISC) (Also called the Petlyuk project. Ended Aptil 1998)
  2. Possible EU project on integrated control and optimization (INCOOP). The project has yet to start officially, but there is a litererature survey on nonlinear MPC which was prepared earlier.

See the Annual Reports for more information.