The following discussion is part of an occasional series, "Ask the Automation Pros," authored by Greg McMillan, industry consultant, author of numerous process control books, and 2010 ISA Life Achievement Award recipient. Program administrators will collect submitted questions and solicits responses from automation professionals. Past Q&A videos are available on the ISA YouTube channel. View the playlist here. You can read all posts from this series here.

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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

MPC, Fuzzy, or PID? How do you pick the correct solution now that all are available at a lower cost? How do you prevent people from abandoning APC/MPC systems when the expert leaves?   

Greg McMillan's Answer

• If you want a comprehensive optimization of a continuous process the solution is model predictive controller (MPC). Linear programs (LP) and real-time optimization (RTO) need the prediction to violation of constraints inherent in MPC. If you are satisfied with a local piecemeal optimization of fed batch as well as continuous unit operations, PID valve position control is a quick solution. See my article Don’t Over Look PID in APC. Your skill base will also sway the argument. When I did some pH control consulting at a refinery, the manager said they would startup on PID control but convert to MPC within two weeks because they don’t have any Shinskey types. In refineries and large mature continuous processes MPC is the norm. MPC was originally developed by Charlie Cutler at Shell.
• The PID with the deadtime compensation option has been proven by McAvoy and Shinskey to provide the best load rejection. There are many PID options under- utilized, such as dynamic reset limiting, setpoint velocity limiting, the enhanced PID for wireless (PIDPlus), adjustable alpha and beta factors, and deadtime compensation by the simple addition of a deadtime block. The combination of AO block velocity limits and dynamic reset limiting provides the move suppression found so useful in MPC for limiting the transfer of variability from the process variable to the controlled variable to reduce interaction. If decoupling is needed, a simple feedforward of one PID output to another PID output can help. Chapter 14 explores many PID opportunities in the book PID Control in the Third Millennium: Lessons Learned and New Approaches.
• A PID can be set to do better than a fuzzy logic controller via use of the extensive PID options and a Full Throttle Batch and Startup Response.
• Jim Cahill recorded 12 live demo-seminars called "deminars" showing the use of the website for PID control solutions.
• In my ISA pocket guide Models Unleashed, I compared the performance of the MPC and PID and found the MPC to be much more sensitive to changes in process dynamics. An overestimate of the loop deadtime makes an MPC unstable where it just makes the PID sluggish from slower tuning based on the larger deadtime. I also found that deadtime compensators were adversely affected by changes in dynamics similar to the MPC.

• Shinskey and I found that the improvement and robustness of deadtime compensation greater for a process dominated by a lag (t) rather than a deadtime (q) (deadtime compensation works best for t >> q), contrary to public opinion and what is often stated in the literature. Note that the term lag is commonly used for time constant.
• An APC solution using PID is much more likely to stay in-service once the expert leaves the building because the PID is familiar to the operator and configuration engineer-technician. In a plant with mostly PID, you need to have more training for an MPC.

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• In general the most powerful way to keep a control solution in-service is to provide online process metrics showing the dollar benefits with a capture of “before” and “after” cases. Normally, the best way to show this is a cost per pound or kilogram of intermediates or product (e.g. raw material or energy dollar cost per pound). Get with a process engineer to develop the calculations. Production rate should also be computed to show benefits from capacity related benefits (e.g. dollar profit per pound product) and to monitor capacity effects on costs. Synchronize input flows (e.g. utilities and raw materials) to output flows (e.g. intermediates or products) by passing the input flows through a deadtime and filter block. Filter the final calculation to eliminate noise and inverse response. Modes and setpoints should be trended with metrics and suspend an update of metrics when the unit operation is shutdown. If you can’t get agreement on costs and prices, simply compute a ratio of a key output to an input.

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.

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