Modeling and Control

To blog or not to blog, that is the question. When on vacation, I choose not to. Now I am back and ready to blog on. Here are some myths from my days (and nights) at Monsanto improving pH loops.

(16) More frequent buffer calibrations improve pH measurement accuracy – unless an electrode needs to be removed to be cleaned, it is better to leave it in the process and do an adjustment based on a statistical average of process samples. The buffer is not representative of the process in terms of liquid junction potentials and the glass electrode response especially when the process has salts or strong acids and bases. The reference electrode can take up to a day to reach equilibrium with the process when it is reinserted. Also, wiping the glass electrode or soaking it in cleaning solutions reduces its life expectancy. Finally, the effect of temperature on pH is not found via a buffer which leads to the next myth.

(17) The pH electrode temperature compensator corrects for changes in pH with temperature – the standard temperature compensation is the change in millivolts per pH unit per the Nernst equation. The change in the actual solution pH due to the change in dissociation constants with temperature requires another correction. Many smart pH transmitters now have this solution pH temperature compensation but it is up to the user to find the relationship. Information on how the dissociation constants change with temperature and how this would affect a complex solution is scarce to nonexistent so it requires a pH sample’s temperature to be varied in the lab. For the simple case of water and a strong base (e.g. caustic) where the effect is dominated by the change in the water dissociation constant with temperature, the error is about -0.03 pH per degree C.

(18) A second pH electrode always improves measurement accuracy and reliability – a second electrode offers more questions than answers since they never agree unless you are lucky enough to have a problem that a smart transmitter can detect. Every operator has a favorite electrode based on some interesting war stories but its anybodies guess as to which is right. Also, since electrodes can fail or develop errors in almost any direction, a decision to select the best electrode requires some extra intelligence such as changes in electrode resistance or a comparison of response times. At Monsanto we used middle signal selection of three electrodes to automatically and inherently ride out a failure of any type and reduce the noise and short term errors for concentration gradients.

(19) The rangeability of a control valve is per catalog specifications – the rangeability statements by valve suppliers usually does not take into account the stick-slip near the closed position. Many rotary valves carry impressive rangeability statements but don’t deliver the goods because the control at low flows is a big saw tooth from high seal friction and breakaway torque.

(20) A valve with a positioner is a good throttling valve – the response of a control valve depends upon the entire package (valve, seat, seal, actuator, packing, positioner, and feedback mechanism). Putting a positioner on an on-off valve (e.g. block or isolation valve) does not make it a throttling control valve. In fact the feedback mechanism may be lying to the positioner in which case the smart diagnostics mean nothing. For more info on this check out the article “Improve Control Loop Performance”

I have “Final Four” on my mind and I am off to see if my alma Mata Kansas can upset UNC but before I go, if you ever come to Austin check out the Oasis for sunsets and its new Starlight bar for star gazing over Lake Travis. I spent last night at the Oasis Starlight listening to the Eggmen (a great Beatles cover band) and having flashbacks to the 1960s and 1970s. Too bad I didn't wear my plaid bellbottoms.

We conclude with the following myths from Appendix D in my guide Models Unleashed - Virtual Plant and Model Predictive Control Applications published by ISA, 2004.

(21) You need an advanced degree to do advanced control. Not so anymore. New software packages used to form a virtual plant automate much of the expertise needed and eliminate the need for special interfaces. The user can now focus mostly on the application and the goal.

(22) Dynamic simulations and model based control are only applicable to continuous processes. Since most of the applications are in the continuous industry, this is a common misconception. While it is true that a steady state simulation is not valid since there is by definition no steady state in batch, dynamic simulation can follow a batch as long as the software can handle zero flows and empty vessels. Model predictive control (MPC), which looks at trajectories, is suitable for the optimization of fed batch processes during particularly important points in the batch cycle. The opportunities to improve a process’s efficiency by MPC are about 25% for batch compared to 5% for continuous operations.

(23) You need consultants to maintain models and advanced control systems. No longer necessarily true. The ease of use of new software allows the user to get much more involved, which is critical to make sure the plant gets the most value out of the models. Previously, the benefits started to drop as soon as the consultant left the job site. Now the user should be able to tune, troubleshoot, and update the models.

(24) You don’t need good operator displays and training for well designed advanced control systems. The operators are the biggest constraint in most plants. Even if the models used for real time optimization and model based control are perfect, operators will take these systems offline if they don’t understand them. The new guy in town is always suspect, so the first time there is an operational problem and there is no one around to answer questions, MPC systems are turned off even if they are doing the right thing. Training sessions and displays should show the individual contribution of the trajectories of each controlled, disturbance, and constraint variable to the observed changes in the manipulated and optimization variables.

(25) You need to know your process before you start a model based control system application. This would be nice, but often the benefits from a model stems from the knowledge discovery during the systematic building and identification procedures. Frequently, the understanding gained from developing models leads to immediate benefits in terms of better set points and instruments. The commissioning of the MPC is the icing on the cake and locks in benefits for varying plant conditions.

I dug up the following myths from my April 2006 Control Talk column in Control Magazine. I am into recycling and going green. In fact these myths may be a bit moldy.

(26) Auto tuners can compute controller tuning settings with an accuracy of more than one significant figure. Act surprised when unmeasured disturbances, load changes, valve stick-slip, and noise cause each result to be different. Look forward to the opportunity to play bingo with the second digit.

(27) You can just dump all your historical data into a neural network and get wonderful results. Forget about the same stuff that cause auto tuners to have problems and use variables drawing straight lines because anything that smooth or well controlled must be important. Use the controlled variables (process variables) instead of the manipulated variables (controller outputs). Don’t try to avoid extraneous inputs or identification of the control algorithm instead of the process. If you want to purse a career in data processing, use every variable.

(28) Models can predict a process variable that is not measured in the field or lab. Great way to spur creativity in training a neural network and validating a first principal model plus it has the added bonus of the model never being wrong. Wait till your customers figure out something is wrong with the composition of your product. Discount as hearsay any suggestions that even the best models need periodic correction.

(29) To reduce variability in process outputs (temperatures and compositions), keep all the process inputs (flows) constant. Keep believing that you can fix both the process inputs and outputs and don’t accept the notion that process control must transfer variability from process outputs to process inputs to compensate for disturbances.

(30) Positioners should not be used on fast loops. This was true for the good old days of pneumatic positioners and analog controllers. Surely, digital positioners with tuning settings and digital control system scan times can’t make the original theoretical concerns less important than the practical issues of real valves. If you would rather believe the controller outputs are the actual valve positions, and just want valve problems to slip by, save some bucks on your project and only put positioners on slow loops. Just don’t stick around for start up.