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e-tuned by a knowledgeable instrument technician. During this period, the
temperature control of the glass would be poor and the yield of acceptable
containers would be reduced. By comparison, the adaptive controllers have
often been able to stabilize glass temperatures in less than 2 hours and have
not required adjustment to maintain performance.
Forehearth 22-2 has about 15 job changes per month. The improved control
saves approximately 30 hours/month or 360 hours/year of lost production due
to the glass temperature not being stabilized at setpoint. This is about 4% of
the annual production of forehearth 22-2.
The ultimate control performance comparison between the existing PID
controllers and the adaptive controllers is their effect on the production of
acceptable glass containers. Over the last 2 years of operating experience, the
plant has observed an improvement in the Standard Pack of 3.75% to 20%
for the most common containers produced on forehearth 22-2. Assuming a
production rate of 200 containers per minute with a cost of $0.02 per container,
this represents a production increase worth $80,000 to $420,000 per year.
1.8 Conclusions and lessons learned
The main difficulty in designing a predictive controller is to obtain an accurate
model and further to tune a multitude of parameters available in the algorithm.
We have found that, with experience, systematic tuning procedures based on
theoretical results were developed. Also the number of parameters involved in
the controller can be reduced to a manageable amount. Moreover, using the
Laguerre modelling technique, it is possible to obtain satisfactory controller
performance even if at startup the predictive controller is based on a very
simple model.
When users’s choice is to have the learning off robust performance for the
controller is achieved via de-tuning the controller’s internal model. Further,
when particular levels of robust performance are required, in the absence of
learning and against large plant perturbations, a multi-model approach is employed
with success to ensure satisfactory performance.
The constrained optimization characteristic for most of the predictive controllers
is replaced with success by an antiwindup scheme. This approach is
reducing the computation time sufficiently to allow real-time constrained operation.
Since progress has been observed in the efficiency of solution algorithms and
in the power of the hardware on which they run we can advocate sample time
for the commercial controller as low as 0.1 s for 32 simultaneous MISO loops.
Acknowledgements
The work referred in this Chapter has been transformed into a commercial
product with the exceptional effort of Sava Kovac of Universal Dynamics Technologies
Ltd.
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