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How to Tune a Temperature Control Loop When Auto-Tuning Takes Too Long

 

The following technical discussion is part of an occasional series showcasing the ISA Mentor Program, authored by Greg McMillan, industry consultant, author of numerous process control books, 2010 ISA Life Achievement Award recipient and retired Senior Fellow from Solutia Inc. (now Eastman Chemical). Greg will be posting questions and responses from the ISA Mentor Program, with contributions from program participants.

 

In the ISA Mentor Program, I am providing guidance for extremely talented individuals from countries such as Argentina, Brazil, Malaysia, Mexico, Saudi Arabia, and the USA. This question comes from Hector Torres of Mexico.

 

Hector Torres is a senior process and control engineer for Eastman Chemical Company in Tlaxcala, Mexico, with more than 20 years of experience.

 

Hector Torres’ Question

How do you tune a temperature control loop when auto-tuning takes too long?

 

Greg McMillan’s Answer

I suggest the near-integrating method where you just identify the deadtime and initial ramp rate. This can reduce the test time by 94% as demonstrated in my Demo-Seminar (Deminar #6). The method can also be used to identify a feedforward deadtime and ramp rate for the estimation of the feedforward gain and dynamic compensation based on the difference in feedback and feedforward dead times and near-integrating process gains.

You need to increase the integral time for an integrating process when the controller gain is set much less than what is allowed for maximum disturbance rejection. Most loops on integrating processes are using much less than the allowed controller gain because a higher controller gain causes rapid large movements of the output that scares operations or upsets other loops,

Often a simple AO block or setpoint velocity limit with the dynamic reset limit option solves the actual or perceived problem. If the controller gain is decreased, the integral time must be proportionally increased to retain the optimum product of the controller gain and integral time to prevent slow rolling oscillations. Most control theory books and most people don’t realize that this counter intuitive relationship where increasing the controller gain allows you to decrease the integral time.

From the control literature, we are familiar with the situation where too high of a controller gain (too much proportional action) or too low an integral time or reset time (too much integral or reset action) will cause oscillations and overshoot.  In integrating responses, too large of an integral time or too small of a controller gain can cause oscillations and overshoot as well. While the oscillations are not as dramatic as going unstable, the effect is significant and confusing for integrating processes.

For runaway processes as encountered with highly exothermic reactors (e.g. polymerization reactors), too low of a temperature controller gain can cause a dangerous runaway. Tests in manual for identification of dynamics and tuning are often not permitted because the temperature response can accelerate reaching a point of no return. Fortunately, the near integrator tuning method works well here with the controller in automatic for a setpoint change. The high controller gain and high integral times for these reactor temperature loops causes a step change in the controller output useful for the near-integrator method.

The user must take into account the effect of engineering units on tuning settings.  Reset settings have time units that may be different than what is used in the identification of the loop deadtime and ramp rate. The reset setting in repeats per second is the inverse of the reset setting in seconds. A controller gain should be dimensionless.

If the units are per cent for the proportional mode tuning setting, the setting is likely proportional band that is 100% divided by a dimensionless controller gain. Nearly all PID algorithms work on percent inputs and outputs despite the operator trend, graphics, and faceplate being in engineering units. To compute the controller gain the PID process variable, setpoint, and output must be converted to percent signals based on scale ranges. Thus, scale ranges affect the controller gain setting.

There have been some rare cases of a PID algorithm in a programmable logic controller (PLC) working in engineering units resulting in very bizarre controller gain settings.

 

Additional Mentor Program Resources

See the ISA book 101 Tips for a Successful Automation Career that grew out of this Mentor Program to gain concise and practical advice. See the InTech magazine feature article Enabling new automation engineers for candid comments from some of the original program participants. See the Control Talk column How to effectively get engineering knowledge with the ISA Mentor Program protégée Keneisha Williams on the challenges faced by young engineers today, and the column How to succeed at career and project migration with protégé Bill Thomas on how to make the most out of yourself and your project. Providing discussion and answers besides Greg McMillan and co-founder of the program Hunter Vegas (project engineering manager at Wunderlich-Malec) are resources Mark Darby (principal consultant at CMiD Solutions), Brian Hrankowsky (consultant engineer at a major pharmaceutical company), Michel Ruel (executive director, engineering practice at BBA Inc.), Leah Ruder (director of global project engineering at the Midwest Engineering Center of Emerson Automation Solutions), Nick Sands (ISA Fellow and Manufacturing Technology Fellow at DuPont), Bart Propst (process control leader for the Ascend Performance Materials Chocolate Bayou plant), Angela Valdes (automation manager of the Toronto office for SNC-Lavalin), and Daniel Warren (senior instrumentation/electrical specialist at D.M.W. Instrumentation Consulting Services, Ltd.).

 

About the Author
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:

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Image Source: Wikipedia

 

Greg McMillan
Greg McMillan
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 "New Directions in Bioprocess Modeling and Control Second Edition 2020" and "Advanced pH Measurement and Control Fourth Edition 2023." Greg has been the monthly "Control Talk" columnist for Control magazine since 2002. Greg has recently retired as a part-time modeling and control consultant in Technology for Process Simulation for Emerson Automation Solutions specializing in the use of the digital twin for exploring new opportunities. Greg received the ISA Mentoring Excellence Award in 2020 and the ISA Standards Achievement Award in 2023.

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