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Feb
22

Common Control Myths – Part 1

Process control is rich with mythology probably because what happens in the field is pretty remote from what was described in control text books. It is best summed up by a button given to me by my daughter 25 years ago that says “Reality Reeks.” Here are some myths that come to mind this Friday evening after updating a simulation library whose main threat is reality.

(1) Decreasing the scan time will improve control – for slow processes and older DCS with 12 bit A/D for I/O, the faster scan reduces the signal to noise ratio. This was particularly a problem for temperature loops that used thermocouple input cards with large spans. Often the noise from A/D chatter precluded the use of rate action even though these loops had significant second order time constants. The more prevalent reason a reduction in scan time may have no impact on control is the implied dead time from the use of current tuning practices as seen in the next myth. You can estimate how much dead time you can add before you see an increase in integrated absolute error for a load disturbance. Next week I will show the development of the equations that predict the implied dead time and the impact on peak and integrated error when the dead time added causes the total actual dead time to exceed the implied dead time. The dead time for a load upset from an unsynchronized scan time can be estimated to be on the average the latency plus one half of the scan time.

(2) Controllers are tuned for rapid set point response – controllers are tuned slower than what is shown in nearly every academic paper and book. This slower tuning creates an implied dead time that is greater than the actual dead time. Intuitively you can visualize this effect by considering as the tuning is slowed down more and more, the loop approaches manual control where the dead time for automatic corrective action is infinite. Whenever articles show the improvement from reduced dead time, the controller is retuned for best response to take advantage of the better dynamics.

(3) Unmeasured disturbances are a side issue – if there were no unmeasured disturbances, control would be a non issue because you could home in on the controller output that corresponds to the desired set point for a process variable. You would just need to run some data fitting algorithm one time and the loop would be set for the life of the process. In reality, there are always unmeasured disturbances.

(4) Disturbances enter directly into the measurement – in almost every process I have worked on the disturbance gets into the loop via a process input. For example, changes in raw materials to a reactor are feed inputs that go through the mixing and reaction process before they appear in the reactor temperature. If the upset enters downstream of the process, it is noise to me.

(5) Disturbances are step inputs – this is the case for almost every published analysis of control loops but in the real world, except for on-off control, there is nearly always a load disturbance time constant whether it is due to reset action in the culprit controller or the mixing time of a volume (even unagitated vessels have some degree of dispersion even if it just from temperature or concentration gradients).