Common automation myths debunked

Getting to the truth about deadtime, rangeability, valve performance, positioners, lambda tuning, controller gain, fuzzy logic and neural networks

By Gregory McMillan

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There are a lot of misconceptions in the application of automation systems in the process industries. Sometimes these errors in thinking don’t cause much harm because good design practices keep the user out of trouble, but they keep us from the truth and a better understanding. Years of allegiance may be attached to these false ideas without analysis, putting them in the category of myths. Here, I expose the common myths with hope that we can move on to address the real issues in process control.

Myth: Deadtime-dominant processes should use model-predictive control (MPC)

Deadtime-dominant processes can achieve tighter control by using Shinskey’s PID plus deadtime compensator (PID+TD), achieved by simply inserting a deadtime block in the external reset path and tuning the PID much more aggressively, particularly in terms of reducing the reset time.

If the PID tuning is left at its original value before deadtime compensation, loop performance may actually be lower after deadtime compensation. While a Smith Predictor can achieve a similar improvement, PID+TD only needs identification of the total loop deadtime for deadtime compensation, whereas the Smith Predictor requires this plus identification of the open-loop gain and open-loop time constant. Note that the deadtime can be updated in a PID+TC but not necessary in an MPC, which is particularly important when the deadtime is extremely variable (e.g., transportation delay).

The inability of users and some tuning software to identify the dynamic compensation for feedforward signals has pushed applications into using MPC because the dynamics of disturbances are automatically identified and included in the dynamic matrix. For deadtime-dominant systems, the time constants (lags) in the manipulated variable and disturbance variable path are similar and small. This reduces the need for a lead/lag block in the dynamic compensation of the of the feedforward signal normally used to make sure the feedforward correction arrives at a common point in the process at the same time as the disturbance. All that's needed to ensure feedforward does not arrive too soon is simply inserting a deadtime block in the feedforward signal.

It's not commonly appreciated that lag-dominant processes can potentially see the greatest improvement from a PID+TD or MPC. Since PID control is often excellent for these loops, if the process is treated as near-integrating and integrating process tuning rules are used, there's not as much need seen for something more than a simple PID. The real need for MPC shows up for compound complex process dynamics, exact feedforward dynamic compensation, full decoupling of interactions, constraint control and optimization.

White paper: How to specify valves and  positioners that don't compromise control

Deadtime-dominant processes are more sensitive to a misidentification of the total loop deadtime, with the sensitivity being greater for a deadtime estimate that's too large rather than too small. For plain old PID, an estimate of a deadtime that's too large just leads to sluggish control. In PID+TC and MPC, an estimated deadtime that's too large can cause oscillations.

The best solution for deadtime-dominant processes is to try to reduce the total deadtime. If most of the deadtime comes from an analyzer or wireless device, a faster cycle time and update time will greatly improve the integrated error by enabling the PID to see disturbances sooner.

Also, an enhanced PID that uses external reset feedback and doesn't update the controller output until the process variable or setpoint changes can greatly simplify tuning by making it more aggressive and independent of changes in the process time constants. The PID gain can be as large as the inverse of the dimensionless open-loop gain for self-regulating processes, and the reset time can be reduced to be the other sources of deadtime, often due to automation system and transportation delays. For example, if the open-loop gain is 2, and the transportation source of deadtime is 20 seconds, the controller gain setting can be as large as 0.5 and the integral time (reset time) setting can be as small as 20 seconds. For more on this enhanced PID, see the July 16, 2015 “Control Talk” blog, “Batch and Continuous Control with At-Line and Offline Analyzer Tips.” For much more about deadtime-dominant processes, see the Dec. 1, 2016, “Control Talk” blog, “Deadtime Dominance—Sources, Consequences and Solutions.”

A side issue here is that you can prove almost any point, including the benefit of a special algorithm, by not testing the controller for unmeasured disturbances that can arrive anytime in the controller execution time, not tuning the PID as aggressively as possible, and not using options, such as adaptive tuning and external reset feedback, enabling the PID+TD and enhanced PID.

Myth: Valve rangeability is determined by accuracy of inherent flow characteristic

The traditional definition of valve rangeability being determined by how accurately the inherent flow characteristic matches a theoretical flow characteristic is largely bogus and a distraction at best. The process controller will correct for any mismatch and there are much greater issues. The actual flow rangeability depends on the installed flow characteristic, and backlash and stiction near the closed position. As less of the system pressure drop is allocated to the control valve to save on energy, the installed flow characteristic of a linear trim valve distorts to quick-opening. The backlash and stiction that's greatest near the seat, and expressed as a percent of total valve stroke, translates to greater error in the flow due to the steep installed flow characteristic near the closed position.

The amplitude of limit cycles from stiction is increased due to the greater valve gain (and hence, open-loop gain) that's the product of the valve gain, process gain and measurement gain. The amplitude of limit cycles from backlash is greater because the controller gain must be reduced due to the larger open-loop gain. Limit cycles develop from stiction if there are one or more integrators in the loop that includes the process, valve positioner and PID controller. Limit cycles develop from backlash if there are two or more integrators in the loop. Processes that have an integrator (integrating process response) include level, gas pressure and batch composition.

The installed flow characteristic of an equal-percentage valve gets flatter, but the minimum flow coefficient gets larger, as the portion of the system pressure drop allocated to the valve gets smaller. Thus, the best rangeability is achieved by a control valve with larger portion of the system drop allocated as valve pressure drop and a sliding stem valve with a sensitive diaphragm actuator and a sensitive, well-tuned smart positioner (e.g., a real throttling control valve), which sets us up for the next two myths.

Myth: High-performance valves give high performance

The term “high performance” has been used for control valves with minimum leakage. These valves are often on-off or isolation valves posing as control valves. They have very low leakage but crummy response due to the higher seat and seal friction near the closed position, higher backlash from linkages for rotary valves, and the types of piston actuators. Often, the positioner is being lied to because the positioner sees actuator shaft position and not the position of the internal flow element (e.g., plug, disk or ball).

The positioners used often have poor sensitivity that shows up as an order-of-magnitude or greater increase in 86% response time (T86) for small steps in valve signal, particularly when they're reversed (e.g., T86 of 80 seconds for 0.2% step versus 4 seconds for 20% step). Unfortunately, valve specifications have nothing about valve response (e.g., deadband, resolution and T86) or its effect on rangeability. What's on the valve specification is leakage. To make matters worse, these so called high-performance valves are less expensive than a real throttling control valve.

Myth: Valve positioners should use integral action

Positioners have traditionally been high-gain, proportional-only controllers. If a high-gain, sensitive, pneumatic relay is used, position control can be quite tight since the offset from setpoint for a proportional-only controller is inversely proportional to the controller gain. The offset is also of little consequence, since the effect is rather minor and short-term, with the process controller correcting the offset. What the process controller needs is an immediate, fast, total response. There are much larger nonlinearities and offsets that the process controller has to deal with.

Want to read more from Greg? Read his Control Talk blog.

The original idea of cascade control is to make the inner loop (in this case, the positioner) as fast as possible by maximizing inner controller gain, which means going to proportional or proportional-plus-derivative control. Integral action in the inner loop is hurtful unless we're talking a secondary flow loop for ratio control or feedforward control. The advent of smarter positioners has led to much more complex control algorithms that include integral action. The use of integral action may make the valve step response tests look better, with the final position more closely matching the signal. Not realized is that the positioner gain had to be reduced, and that integral action in the positioner increases the instances of limit cycles.

In fact, with the process controller in manual (positioner signal constant), a limit cycle will develop from stiction in the valve unless an integral deadband is set. Also, the increase in the number of integrators in the control system means that the process controller with integral action will develop a limit cycle from backlash since there are now two integrators. So here we have the common situation where an attempt to make appearances look better has created a problem. Many positioners now come with the integral action turned on as a default.

For much more on these myths about control valves, see the May 1, 2016 “Control Talk” blog, “Sizing Up Valve Sizing Opportunities,” and the article, “How to specify valves and positioners that don’t compromise control.”

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  • Reading your article, topics concerning Artificial Neural Networks and Fuzzy Logic Control, a doubt came: the applications we have (or had) wasn't implemented without enough knowledge about the tools and the process? My doubts is because sometimes, for market reasons, some people promises miracles without any scientific bases. I learned that we should use simpler solutions instead looking for the novelty because itself! Algorithm for Fuzzy logic control that I saw the implementation in PLC and DCS was so simple and the only thing they tried was mimic PID. Why use then instead using PID? In the other hand I know about implementations of neuro-fuzzy controllers that overcome the PID performance. That applications you can not see so often but there are process demands that requires some sort of solution beyond "normal" PID. I believe such solutions are complex but modified PID solutions are as well.

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