Enhanced Model Based Process Control

Retrofitting Moisture Control

The Dryer Master approach to adaptive model based control (Enhanced GMC) began as an attempt to control a notoriously difficult process – grain drying.

Drying grain is one of the most challenging control tasks there is. Not only can you have wide variances in incoming moistures, but you can also have drying conditions that change throughout the day as the weather changes.

Because there are so many variables and changing factors in the grain drying process it was not possible to build a controller that could account for all of them individually. Instead the idea was developed to design a controller that would be able to model each individual dryer as a whole and then be able to continually adjust the model as drying conditions changed. The result is a robust controller that is continuously "learning" about the process.

There is no easier or better way to understand Dryer Master's model based control than to see it in action.

The graph below provides a picture of 20 hours of corn drying.

In the lower part of the graph the orange line is the percentage moisture of the grain going into the dryer - collected from the Dryer Master in-line moisture sensor, sampling at 6 times per second. The red line is the moisture of the grain exiting the dryer, again as measured by a Dryer Master moisture sensor. The straight black line is the target moisture, as set by the dryer operator. In this case it is 15.5%.

In the upper part of the graph the green line shows the control actions taken by the Dryer Master as it adjusts the metering roll speed (discharge rate) of the dryer as it tries to dry as much grain as close to target as possible. Let us look at two specific areas of the graph to observe how Dryer Master control works, on two difficult control challenges.

Graph showing moisture control

Point 1:

At point 1, the moisture sensor at the inlet to the dryer (orange line) picks up the steep drop in the incoming moisture (from 25% down to 20%), and feeds this information to the Dryer Master controller. The controller uses this new information, and its knowledge of what is already in the dryer, to decide to increase the discharge rate (green line). A short while later when the inlet moisture increases again the controller slows the discharge rate back down.

The result can be seen approximately 2 hours later (one dryer load) in the outlet moisture. Although the 20% corn comes out slightly below the target moisture, it is much closer to target than if the Dryer Master had not sped up the discharge rate.

The Dryer Master has made the best of a very difficult situation, a situation that an operator, using only manual samples taken from the dryer outlet, might not even have been aware of until after the fact.

Point 2:

At point 2, the inlet moisture jumps back up from 22% to 27%. The Dryer Master again sees this and gradually adjusts the discharge rate, but this time slowing it down. This results in some of the 22% grain eventually coming out slightly below target, and then some of the 27% grain exiting slightly above target.

Overall, because the moistures are centered around the target, once the grain is in storage and has a chance to temper, the average moisture will be very close to the operator's target moisture.

Drying Strategy:

Note that the Dryer Master does not just pick a discharge rate for a specific moisture. Each control decision weighs the incoming moisture, the moisture of the grain already in the dryer and the current drying conditions. For example, after 2:00 there is a gradual decrease in the moisture going into the dryer. In response, the Dryer Master also gradually increases the discharge rate. The result is more grain dried closer to target.

Without the moisture information from the Dryer Master the operator may have had to wait until the lower moisture grain came out of the dryer overdried, and was identified in a manual sample, before he would have made a rate adjustment.

The Bottom Line Result:

Dryer Master control helps the facility process more product closer to target. In many instances the reduced variation and the increased closeness to target allows the facility to raise their effective target and in so doing achieve real bottom line savings. For example, if a grain facility with Dryer Master can dry corn to a 15.5% average moisture target instead of a pre Dryer Master effective target of 14.5%, the facility would achieve a 1% increase in yield, and would reduce energy costs and improve dryer throughput at the same time.

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