Where have all the instrument and process control engineers gone? Are they in Florida enjoying golf and the weather, are they filling in part time for a contract engineering design job oblivious to the ice or snow storm, or are they like me venting into the blog sphere?
It is easy for plants to forget about people responsible for the tuning and performance of the loops. The few instrument engineers and process control engineers left are focused on buying transmitters and configuring the DCS, respectively. They do not have the time or training to recognize and analyze the tuning and performance of the loops and more importantly it is probably not in their goals. The manager can readily understand that a production unit needs hardware and configuration to make the plant run but to date the opportunity for better tuning and dynamics in the plant is ambiguous at best, which means it is not going to survive corporate downsizing. Studies that show 30% of the loops are poorly tuned and 30% suffer from poor dynamics (e.g. principally valve stick-slip and process transportation delays) are easy to dismiss if there is no onsite data.
Even when loop tuning and performance is on the radar screen, the number of loops assigned to the instrument or process control engineer in a large continuous plant has increased dramatically to hundreds and even a thousand or more. Batch processes have an order of magnitude fewer loops but the ones they have are generally more difficult because there is no steady state (another story).
Astute process engineers who are looking at the loops try to fill in for the missing control people. However, improving loops is probably not in their job description and they usually haven’t had the opportunity to learn about tuning methods, valve resolution and deadband, and even simple process dynamics. These things are not normally taught in a practical manner in chemical or systems engineering, where the focus is on Laplace and Z-transforms to prepare 1-2% of the students to go on to graduate school to major in control theory and become professors. There are exceptions (see my Feb 4 blog on Washington University and the article by Tom Edgar from the University of Texas in InTech last Fall).
A significant part of the value of recent breakthroughs in thinking and online tools is the recognition of the importance and understanding of how the automation system (e.g. valve and sensor) and process (e.g. piping, mixing, and vessel) affects the process dynamics per Advanced Application Note 4, how the dynamics affect the tuning settings, and in turn how the tuning settings affect the performance of the loop.
For those who are tired of reading or have email to do, the takeaway is:
(1) Plant design sets the minimum and maximums of the process dynamics and how these change with operating point of the process and valve, which in turn determines how the tuning should be scheduled
(2) Process dynamics slowly change with aging, fouling, and frosting
(3) Process dynamics rapidly change with throughput and load (most noticeable during startup and turndown) and show up as a change in the valve’s operating point
(4) Valve, pump speed, and sensor resolution limits create a variable dead time
(5) Process dynamics determine the ultimate possible performance
(6) Tuning settings determine the actual achievable performance
(7) All tuning methods end up with about same controller gain for maximum rejection of process load disturbances if there are no extenuating circumstances
(8) The reduction in error for a load disturbance can be simply estimated from tuning
(9) Online tools can identify valve stick-slip, deadband, and the valve characteristic
(10) Online tools can identify the process dynamics and schedule tuning settings
More aggressive tuning increases the rate of change of the controller output and hence decreases the dead time from valve resolution/deadband. While it does not affect the amplitude, it increases the frequency of the limit cycle from valve resolution/deadband. This may or may not be a good thing. A faster cycle is more effectively filtered out downstream by a process volume but a faster cycle may be more disruptive to associated loops on the input to the process volume (e.g. loop interaction). More aggressive tuning setting (e.g. high controller gains) may also amplify measurement noise. Thus, there is a need to monitor the variability of all loops, which is an important feature in online software today.
This is not to say that all loops are tuned sluggishly. We have seen several loops that are oscillating nearly full scale (essentially on-off control) and the users have actually gotten use to this. The process runs moderately well because the average of the oscillations is OK. The oscillations are tough on valves and equipment and tough on the process engineer because he/she cannot see a discernable pattern in the controller output important for diagnosing changes in the process and loads.
Getting back to the more common case of sluggishly tuned controllers, how far off the mark is the controller gain for maximum disturbance rejection in some important loops? A Lambda factor of 2 to 4 is commonly used because this is what is appropriate for the flow, liquid pressure, pipeline, and heat exchanger loops frequently encountered, particularly in pulp and paper. However, for loops on biological or chemical reactors, evaporators, crystallizers, neutralizers, and distillation columns (unit operations distinguished by a high degree of back mixing from bubble flow and/or agitation), a Lambda factor of about 0.2 provides the best disturbance rejection with acceptable robustness because the dead time to time constant ratio is less than 0.2. Note that Lambda is the Lambda factor multiplied by the process time constant so setting the Lambda factor equal to the dead time to time constant ratio corresponds to setting Lambda equal to the dead time. Thus, current tuning practice gives a gain that is ten times too low and thus an integrated error for load disturbances that is ten times larger than achievable for highly back mixed volumes.
Many of these loops behave like they have integrating processes (like level) and may be best modeled as integrating (e.g. “near integrating”) even if they are not perfectly integrating. The integrating process gain is inversely proportional to the back mixed volume.
People are starting to understand this problem and plants may have some how arrived at the more aggressive settings on critical unit operations. It is important to note that to avoid problems with more aggressive tuning during startup and a turndown (lower throughput rates), the controller gain should be identified and scheduled online since the dead time is inversely proportional to the throughput rate and the valve gain (curve slope) changes with operating point on the installed valve characteristic. Also, it may be advisable to institute set point rate limits on primary loops to prevent big steps in the controller output from a set point change.
A final point, if you don’t tune the temperature loop on a highly exothermic reactor aggressively, a runaway can occur due to positive feedback (higher temperature causes a higher reaction rate through Arrhenius equation). Customers have learned the hard way to use a more aggressive controller gain to keep the relief system from blowing. For these reactors there is a lower controller gain limit besides the normal upper limit for stability. There is also a window of allowable controller gains for integrating processes when the controller has integral action (PI or PID), but this is getting too deep.