Plant-Wide Control Approach

Herding Cats: Successfully Manage All Those Process Variables With a Systematic Approach to Plant-Wide Control

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Control," Ind. Eng. Chem. Res, 48 (44), 10892-10902, 2009.] This means that the inventory in each unit is controlled
locally, that is, by its own inflows or outflows.

In theory, one may not require local consistency, and allow for "long" inventory loops, but this is almost never done for obvious operational reasons, including risk of emptying or overfilling tanks, start-up and tuning and increased complexity.

Plant-Wide Control Overview–Bottom Up

Bottom-up analysis (focus on dynamics) begins with Step 5—Choose structure of regulatory (stabilizing) layer. The purpose of the regulatory layer is to stabilize the plant, preferably using a simple control structure with single-loop PID controllers. "Stabilize" here means the process doesm’t drift away from acceptable operating conditions when there are disturbances. Also, the regulatory layer should follow the setpoints given by the "supervisory layer."

Reassignments (logic) in the regulatory layer should be avoided. Preferably, the regulatory layer should be independent of the economic control objectives (regions of steady-state active constraints), which may change, depending on disturbances, prices and marked conditions. The main decisions are:

  • Identify stabilizing CV2s. These are typically drifting variables, such as levels, pressures, reactor temperature or the temperature profile in distillation column. In addition, active constraints (CV1) that require tight control (small back-off) may be assigned to the regulatory layer. This usually isn’t necessary with tight control of unconstrained CVs because optimum is usually relatively flat. Also, note that we do not "use up" any degrees of freedom in the regulatory control layer because the setpoints CV2 are left as manipulated variables (MVs) for the supervisory layer. To some extent the choices for CV1 and CV2 (Decision 1) are independent of each other.
  • Identify pairings (MVs to be used to control CV2 (Decision 4)), taking into account the following:
  • Ensure "local consistency." You want local consistency for the inventory control [Aske and Skogestad, 2009]. This implies that the inventory control system is radiating around the given flow.
  • Control constraints. You want tight control of important active constraints (to avoid back-off). The main rule is to "pair close."
  • Avoid selecting as MVs, in the regulatory layer, variables that may optimally saturate (steady-state), because this would require either reassignment of regulatory loop (complication penalty) or back-off for the MV variable (economic penalty).

Step 6—Select structure of supervisory control layer. Objectives of supervisory layer:

  1. Switch control structures (CV1) depending on operating region.
  2. Perform "advanced" economic/coordination control tasks: 
  • Control primary variables CV1 at setpoint using as degrees of freedom (MV): Setpoints to the regulatory layer (CV2s)
  • "Unused" degrees of freedom (valves)
  • Keep an eye on stabilizing layer
  • Avoid saturation in stabilizing layer (which usually requires back-off and thus economic penalty)
  • Feed-forward from disturbances (If helpful)
  • Make use of extra inputs
  • Make use of extra measurements

Step 7—Select structure of (or need for) optimization layer (RTO).  Ask the question, is this even necessary? Do we need such a structure?


Alternative 1—"Advanced single loop control" = PID control with possible "fixes," such as feed-forward (ratio), decouplers, logic, selectors and split-range control. (In many cases some of these tasks are moved down to the regulatory layer). With single-loop control an important decision is to select pairings. Note that the issue of finding the right pairings is more difficult for the supervisory layer because the interactions are usually much stronger at slower time scales.

Alternative 2—Multivariable control (usually MPC).


This article presents the current version of the systematic plant-wide control procedure. It’s still being updated and tested on applications, but after having worked on this issue of about 25 years, I have good hopes of converging at final procedure by about the year 2025.

[Editor’s note: An extended version of this article is at] 

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