ISA Interchange

Welcome to the official blog of the International Society of Automation (ISA).

This blog covers numerous topics on industrial automation such as operations & management, continuous & batch processing, connectivity, manufacturing & machine control, and Industry 4.0.

The material and information contained on this website is for general information purposes only. ISA blog posts may be authored by ISA staff and guest authors from the automation community. Views and opinions expressed by a guest author are solely their own, and do not necessarily represent those of ISA. Posts made by guest authors have been subject to peer review.

All Posts

Why You Should Use an Enhanced PID for At-Line and Off-Line Analyzers

 

The following tip is from the ISA book by Greg McMillan and Hunter Vegas titled 101 Tips for a Successful Automation Career, inspired by the ISA Mentor Program. This is Tip #100, and was written by Greg.

 

I have always favored online analyzers because they offer a continuous measurement with minimal deadtime. These analyzers usually have sensors in a pipeline or vessel to directly measure a property of the process, such as capacitance, conductivity, color, density, oxidation reduction potential, particle size, pH, turbidity, and viscosity. Expensive analyzers such as mass spectrometers that serve many vessels do not offer a continuous measurement because a sample or slip stream is cycled through them.

Despite the promise of new technologies, such as Near Infrared (NIR), the workhorse of the process industry is still the gas chromatograph, as discussed in the Control Talk column Process Analyzers. Analyze This! The deadtime introduced by these at-line analyzers is 1½ times the analyzer cycle time (Tip #90) plus the sample transportation delay and multiplex time. The total deadtime from a chromatograph can range anywhere from 30 to 60 minutes.

 

At-line analyzers may be more accurate but present more challenging maintenance and control than online analyzers. At-line analyzers require sample system maintenance and special technician expertise for troubleshooting. Failure to update causes the controller to ramp off toward an output limit when an analyzer measurement is used for closed loop control.

Most raw material and batch compositions are measured off-line in the laboratory. The time it takes the operator to take the sample and the lab technicians to do the analysis and enter the result is typically long and variable.

As a consequence these results are essentially useless for closed loop control with a traditional PID. We have seen the consequences of deadtime (Tip #70 and #71). A traditional PID requires the controller gain to be decreased and the reset time to be increased as the deadtime is increased. Composition controllers that use at-line analyzers must be tuned much slower than temperature controllers on the same equipment. Composition controllers are usually relegated to trimming temperature setpoints. The temperature controller takes care of most disturbances and the composition controller slowly corrects for temperature sensor drift and changes in the equilibrium relationships between temperature and composition. Most of the applications are on slow unit operations, such as distillation that have a time to steady state of 10 hours or more. An enhanced PID opens the door for the use of at-line analyzers and even off-line analyzers on even fast processes and improves the loop performance for all analyzers.

Concept: An enhanced PID does not compute the integral mode contribution until there is an update of the measurement or there is a setpoint change. The exponential response of the external-reset signal is used. The contributions from the proportional and derivative modes also do not change. Consequently, between analyzer updates or for a failure of an analyzer to update for a constant setpoint, there is no change in the controller output. When the deadtime from the analyzer system is greater than 95% of process response time, the controller gain can be as large as the inverse of the open loop gain, and the reset time can be based on the original process dynamics. For the accurate identification of the open loop gain, the controller can make a single correction that compensates for a setpoint change or an analyzer update. Long and variable update times from off-line analyzers do not affect the tuning.

Details: For analyzer applications, use an enhanced PID developed for wireless that utilizes external-reset feedback. If nearly the full process response is seen within the analyzer update interval (analyzer update time > 95% of process response time), the controller gain can be increased toward a maximum that is simply the inverse of the open loop gain. The open loop gain is the percent change in measurement divided by the percent change in controller output after all transients have died out (Tip #89). For cascade control, the open loop gain takes into account the effect of secondary controller scale, process gain, and the analyzer primary controller scale. The reset time can be based on the process deadtime. Use feedforward control for measured disturbances since there is little to no attenuation by feedback control because the effect of the disturbance is not seen until after the analyzer deadtime. Feedforward signal changes immediately change the output. If the analyzer fails to update, the enhanced PID output will not change.

 

Watch-outs: A bizarre analyzer value or an upscale or downscale failure must be screened out. While the enhanced PID simplifies the tuning, the response for unmeasured disturbances still depends upon the total loop deadtime. For fast unmeasured disturbances, the peak error is the open loop error, that is, the error that would appear if there was no feedback control. The minimum integrated absolute error is the peak error multiplied by ½ of the total loop deadtime. For setpoint changes, the rise time will be increased by the analyzer deadtime if the controller gain is less than the inverse of the open loop gain.

Exceptions: Closed loop control will not work for erratic analyzer values or poor signal-to-noise ratios.

Insight: An enhanced PID can simplify the tuning and improve the stability for loops with large and/or variable analyzer update times.

Rule-of-Thumb: Use an enhanced PID with feedback plus feedforward control for at-line and off-line analyzers.

 

About the Authors
Gregory K. McMillan, CAP, is a retired Senior Fellow from Solutia/Monsanto where he worked in engineering technology on process control improvement. Greg was also an affiliate professor for Washington University in Saint Louis. Greg is an ISA Fellow and received the ISA Kermit Fischer Environmental Award for pH control in 1991, the Control magazine Engineer of the Year award for the process industry in 1994, was inducted into the Control magazine Process Automation Hall of Fame in 2001, was honored by InTech magazine in 2003 as one of the most influential innovators in automation, and received the ISA Life Achievement Award in 2010. Greg is the author of numerous books on process control, including Advances in Reactor Measurement and Control and Essentials of Modern Measurements and Final Elements in the Process Industry. Greg has been the monthly "Control Talk" columnist for Control magazine since 2002. Presently, Greg is a part time modeling and control consultant in Technology for Process Simulation for Emerson Automation Solutions specializing in the use of the virtual plant for exploring new opportunities. He spends most of his time writing, teaching and leading the ISA Mentor Program he founded in 2011.

 

Connect with Greg
LinkedIn

 

Hunter Vegas, P.E., holds a B.S.E.E. degree from Tulane University and an M.B.A. from Wake Forest University. His job titles have included instrument engineer, production engineer, instrumentation group leader, principal automation engineer, and unit production manager. In 2001, he joined Avid Solutions, Inc., as an engineering manager and lead project engineer, where he works today. Hunter has executed nearly 2,000 instrumentation and control projects over his career, with budgets ranging from a few thousand to millions of dollars. He is proficient in field instrumentation sizing and selection, safety interlock design, electrical design, advanced control strategy, and numerous control system hardware and software platforms.

 

Connect with Hunter
LinkedIn

 

Greg McMillan
Greg McMillan
Greg McMillan has more than 50 years of experience in industrial process automation, with an emphasis on the synergy of dynamic modeling and process control. He retired as a Senior Fellow from Solutia and a senior principal software engineer from Emerson Process Systems and Solutions. He was also an adjunct professor in the Washington University Saint Louis Chemical Engineering department from 2001 to 2004. Greg is the author of numerous ISA books and columns on process control, and he has been the monthly Control Talk columnist for Control magazine since 2002. He is the leader of the monthly ISA “Ask the Automation Pros” Q&A posts that began as a series of Mentor Program Q&A posts in 2014. He started and guided the ISA Standards and Practices committee on ISA-TR5.9-2023, PID Algorithms and Performance Technical Report, and he wrote “Annex A - Valve Response and Control Loop Performance, Sources, Consequences, Fixes, and Specifications” in ISA-TR75.25.02-2000 (R2023), Control Valve Response Measurement from Step Inputs. Greg’s achievements include the ISA Kermit Fischer Environmental Award for pH control in 1991, appointment to ISA Fellow in 1991, the Control magazine Engineer of the Year Award for the Process Industry in 1994, induction into the Control magazine Process Automation Hall of Fame in 2001, selection as one of InTech magazine’s 50 Most Influential Innovators in 2003, several ISA Raymond D. Molloy awards for bestselling books of the year, the ISA Life Achievement Award in 2010, the ISA Mentoring Excellence award in 2020, and the ISA Standards Achievement Award in 2023. He has a BS in engineering physics from Kansas University and an MS in control theory from Missouri University of Science and Technology, both with emphasis on industrial processes.

Books:

Advances in Reactor Measurement and Control
Good Tuning: A Pocket Guide, Fourth Edition
New Directions in Bioprocess Modeling and Control: Maximizing Process Analytical Technology Benefits, Second Edition
Essentials of Modern Measurements and Final Elements in the Process Industry: A Guide to Design, Configuration, Installation, and Maintenance
101 Tips for a Successful Automation Career
Advanced pH Measurement and Control: Digital Twin Synergy and Advances in Technology, Fourth Edition
The Funnier Side of Retirement for Engineers and People of the Technical Persuasion
The Life and Times of an Automation Professional - An Illustrated Guide
Advanced Temperature Measurement and Control, Second Edition
Models Unleashed: Virtual Plant and Model Predictive Control Applications

Related Posts

Checking In With Mimo, ISA's Large Language Model Trained on ISA Content

Over the summer of 2024, the International Society of Automation (ISA) announced a large language model (...
Kara Phelps Nov 15, 2024 7:00:00 AM

Ask the Automation Pros: The Use of Artificial Intelligence in Process Control

The following discussion is part of an occasional series, "Ask the Automation Pros," authored by Greg McM...
Greg McMillan Nov 12, 2024 4:30:00 PM

Protecting Electrical Terminal Blocks From Tampering

Electrical terminal blocks are a common sight in the automation world. Usually mounted on DIN rail in ind...
Anna Goncharova Nov 8, 2024 10:30:00 AM