Author/Authors :
J.A. Rodriguez، نويسنده , , J.A. Romagnoli and
G.C. Goodwin، نويسنده ,
Abstract :
The objective of this work is to identify a control algorithm that is capable of handling nonlinear behaviour (operating point
dependent) witnessed in most industrial processes. To this end, the proposed solution is that of a supervisory multiple model control
scheme, SMMC. This work demonstrates that the multiple model methodology can be recast into a Supervisory approach,
whereby the supervisor is employed as a selector. This selector (supervisor) identifies the appropriate local-controller from a fixed
family set. Unlike other supervisory techniques a multiple model observer (MMO) is proposed for the selection mechanism.
Switching between local-controllers is accomplished bumplessly through a multiple model bumpless transfer scheme. Consequently,
producing a continuous control signal as the process transverses between different operating regimes. The key issue in this application
is the unique interaction between the local-controllers and the supervisor. This interaction is necessary to ensure global stability
is maintained at all times, especially during switching. In short, the SMMC scheme enables the implementation of linear
control theory, which is well accepted in industry, to standard nonlinear processes. The SMMC approach warrants the control
design to extend beyond normal operating conditions that breakdown when standard linear control techniques are applied. The
above notion is applied to a pilot-scale binary distillation column. In this example the column’s distinct operating points describe
the nonlinear behaviour. The results illustrate that as the distillation column shifted between different operating points the SMMC
self-regulates accordingly. This self-regulation ensures that global stability and performance are maintained at an optimum. The
entire SMMC design was implemented within a PC Windows-NT environment that was interfaced to an industrial DCS system.