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VisSim for Process Control

"High fidelity modeling of large scale projects can be done with VisSim. From a financial standpoint, it's extremely worthwhile to the process control community. There are tremendous cost savings in reduced downtime due to offline tuning and control design as well as operator training."

-- Andy Waite, Senior Designer EnTech Control Engineering

Reference Accounts
- Alcan Rolled Products
- Amoco
- Bethlehem Steel
- Bayer Corporation
- BP Chemical
- Caribou Pulp & Paper
- Champion International
- Dow Chemical
- DuPont
- EnTech Control Engineering
- Foxboro
- General Mills
- Georgia Pacific
- International Paper
- Kaiser Aluminum
- Mead Paper
- Mobil Chemical
- Pharmacia-Upjohn
- Potlatch
- Reynolds Metals
- Texaco
- Weyerhaeuser

DuPont & EnTech Use VisSim/Real Time for Dynamic Process Control Simulation
Authors: Extracted from a paper by Hank Graeser (DuPont) and Andy Waite (EnTech)

In a joint effort, engineers from E. I. DuPont de Nemours and EnTech Control Engineering used Visual Solutions' VisSim control system design software, and its real-time option VisSim/Real-Time, to develop a high-fidelity dynamic simulation model of DuPont's non-woven sheet manufacturing facility in Richmond, Virginia.

The model consists of approximately 31,500 blocks and 250 differential equations and simulates roughly a half dozen interrelated processes. It is used by DuPont's control and design engineers to verify process dynamics during product transitions; develop and tune control strategies; and explore possible design changes to enhance control performance. In addition, system operators train on the model to maintain proficiency and learn new procedures without impacting plant operations.

"High Fidelity modeling of a large scale project can be done with VisSim. From a financial standpoint, itís extremely worthwhile to the process control community. There are tremendous cost savings in reduced downtime due to offline tuning and control design as well as operator training."

According to Hank Graeser, senior engineer at DuPont,"VisSim is a highly intuitive environment for developing large scale high-fidelity process models. The DuPont Spruance model, developed in VisSim, has saved the company an estimated one million dollars to date.We developed the model in a third of the time it would normally take using conventional methods. VisSim's block diagram interface made it easy to document and maintain the model.Every time we use the model for control design and off-line tuning, DuPont saves significant dollars as plant down time is reduced. We also train our operators using the VisSim model."

The Ideal Simulation Software
As DuPont engineers drew up the specifications for the model, EnTech engineers were tasked with finding the best simulation software with which to build it.

The sheer scope of the model, which included the entire DuPont facility 15 tanks; 20 sets of pumps, lines, and valves; refiners; headbox and drainage table; vacuum devices, dryer cylinders, and scanning sensors; and other minutiaewarranted a simulation software package capable of modeling and simulating large, multivariable dynamic processes with a high degree of fidelity.

The software had to be interactive and graphically oriented so that dynamic information could be presented in an intuitive manner. In addition, the block set had to include a complete selection of continuous, discrete, transfer function, Boolean, arithmetic, and I/O blocks.

Other key requirements included the capability to run in simulated time, real time, and continuous time; drive real-time analog and digital I/O; stop and continue simulations; initialize all state variables; and extend the block set with custom blocks written in C, for enhanced speed and additional functionality.

Because system operators would also use the simulation model for training purposes, the ability to create realistic control panels with controller faceplates, dynamic tank levels, and built-in alarms was also important.

Based on these requirements, the simulation software that best met EnTech's needs was VisSim and the VisSim/Real-Time companion software.

Model Design
According to DuPont and EnTech engineers, the DuPont model simulates the outputs of 80 sensors and transmitters and accepts input from 50 controller outputs. In addition, the model provides high integrity dynamics as "seen" through the eyes of the actual sensors and transmitters, with a time constant in the range of about 3 seconds. This means that the truly fast dynamics, such as that of incompressible fluid flow, which typically have time constants of 20 milliseconds, do not have to be solved rigorously. Instead, the equations associated with the pump curves, fluid flow, and control valve characteristic curves can be approximated by solving only the nonlinear algebraic equations.

These "algebraic loops" involve the on-line iteration from the last known flow and are solved using algebraic loop time constants of typically 1 second, which provides an adequate safety margin compared to the high-fidelity specification of 3 seconds.

In the resulting simulation, the time constant spread ranges from a fast value of 1 second to that of the mixing time constant for some tanks of 20 minutes. This time constant spread, even though quite large, means that the simulation avoids some of the pitfalls of "stiff systems of differential equations" which are very difficult to solve numerically.

The final simulation model is organized in a multi-layer format in which detailed simulation subelements collapse into "compound blocks." There are 900 compound blocks, in about six layers, organized in an easy-to-follow, process-oriented layout.

Model Verification
In the testing phase, close to 200 real-time I/O channels were used to validate the model and control hardware. The simulated process runs ten times faster than the real process on a Pentium 100 MHz personal computer, at a simulation step size of 0.5 seconds.

Predicting The Future
The DuPont model is an excellent example of how a dynamic multivariable process control model can be developed and utilized using VisSim and VisSim/Real-Time. Graeser and other DuPont engineers have observed a "close match" between model and actual plant data. Based on these results, they are confident that the DuPont model can be used as a "life-cycle" tool to faithfully predict the effects of future design decisions before modifications are actually made to the plant.

Interview
Andy Waite, Creator of the DuPont Model

May 3rd, 1996

Q: How long did it take you to create the DuPont model?
A: About nine months

Q: Had you been using VisSim before the DuPont project?
A: Yes. About two months.

Q: What modeling tools had you used prior to VisSim.
A: Tutsim and Labview, though Labview isn't really simulation software.

Q: Could you have done this project with those tools?
A: No way!

Q: What was the most interesting part of the project?
A: Good question. I'd have to say when we verified the model with actual plant operation. I was totally surprised at how close the model was to the actual plant output. Many of the unit operations were dead on. I didn't have to retune at all! There was one case where the subsystem had six inputs and the actual output looked to be swamped with noise. I figured it was all stochastic. Then the model mapped exactly onto the crazy output. It was very gratifying.

Q: What was the worst part?
A: Converting our 16-bit DLLs to 32-bit was a pain, though we did rely on Bill at VSI for of lot of that. The other pain was getting the model to run numerically stable with a 0.5 second step size. We had to create a custom first-order filter block to solve flow/pressure loops.

Q: What would you do differently?
A: On the next job, I'd use predefined approaches based on our DuPont experience. I'd say the next job should take about half the time this one did.

Q: Is the approach you took typical in the industry today?
A: No, I don't think so. A lot of folks take a pure PDE (partial differential equation) approach, and only try to solve a small piece of the overall system. Nobody has really attempted to model the whole system from first principles, nonlinear warts and all, from an ODE (ordinary differential equation) standpoint, and get the excellent results in real-time that we have seen.

Q: So we give you a platform for easy creation of complex systems?
A: Absolutely!

Q: How long did you spend validating the model?
A: We're not done yet, but I'd say we spent about 20% of our time validating the model against measured data sets. It was very time consuming. We use multiple channels of 16,000 points per channel. On my old 486, with 16-bit VisSim, it took quite a while to adjust a parameter and rerun the simulation. Things improved dramatically with VisSim/32 and my new Pentium.

Q: How did you go about modeling something like valve?
A: I had the choice of using the manufacturer's specs or measuring flow and pressure drop, and calculating the CV curve myself. When I used the latter method, I used a VisSim map block to do a look-up to get the curve right. I did have a little trouble getting enough points in the curve so the piecewise linear look-up would give an accurate answer.

Q: Do you find that actual CV curves differ from the manufacturer's spec?
A: Yes. Sometimes it would be off as much as 20-30%.

Q: How applicable is the large scale system modeling to the process industry?
A: Very. It gives process control engineers the ability to design controls and evaluate control changes to a process prior to implementation. It works both on-line and off-line. Off-line, you can tune up your DCSs and PLCs with a high degree of confidence with a model like this one. On-line, if you see unexpected variance between plant output and model output, you know you have a problem in the plant, and model will tell you where to look. From there, you just work backward from the output display that shows the variance and see where in the model the variance begins. You can then easily find the plugged line or clogged screen on the plant floor.

Q: What about using "soft sensors" in your models?
A: Sure. A soft sensor is something that a high fidelity model like ours can give you. Let's say you have a VisSim model that realistically represents plant behavior, but there is a part of the process that you just can't physically get a sensor to. Just "right-click" on the part of the model that corresponds to the piece you want to measure. As long as the model is running in real-time and is being fed actual plant inputs, you can use any of VisSim's displays to give you the values that a real sensor would normally provide.

Q: What conclusions can you draw from this experience?
A: High fidelity modeling can be done on a large scale! And, from a financial standpoint, it's extremely worthwhile to the process control community. There are tremendous cost savings in reduced downtime due to off-line tuning and control design, as well as operator training.