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How to Maximize Loop Coordination and Optimization


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 #72, and was written by Greg.


As a modeling and control specialist in the engineering technology department of a large chemical company, I was called in to solve difficult and persistent problems that had plagued the production units. I focused mostly on important individual loops in key unit operations, such as gas pressure loops for furnaces and headers, temperature loops for reactors and kilns, surge loops for compressors, level loops for boiler drums and surge tanks, pH loops for all types of equipment and streams, dissolved oxygen loops for bioreactors, polymer pressure loops for extruders, and thickness control loops for sheets. Except for headers, kilns, plug flow reactors, gas reactors, and sheets, problems with interacting loops were minimal.


I could focus on individual loop performance and on transferring as much variability as possible from a key process variable (PV) to its manipulated variables. Even for unit operations with interacting loops, a simple half decoupler with the feedforward of one loop output to another loop output would usually suffice. In distillation, my associate Tolliver did not need to do much in the way of decoupling because there was usually only one temperature loop. Two point composition control, that is, control of top and bottom composition by temperature, was rarely needed.    

I generally did not have to worry about coordination or the movement of a manipulated variable affecting another loop. I could go for the gusto. For optimization, I simply used valve position controllers (VPC) to maximize feed by pushing coolant, vent, and feed valves to a maximum throttle position (Tip #97). I also used VPC to maximize the use of waste fuels and reagents by pushing an expensive fuel or reagent valve with good process dynamics to a minimum throttle position. In petroleum refining, the gas furnaces and catalytic reactors have interactions and don’t have much back mixing reducing the advantage of the PID.

There is a greater need for plant-wide optimization. Because of incredibly large plant capacities, a fraction of a percent improvement in efficiency or production rate translates to huge increase in profitability in an industry where margins are squeezed. Consequently, MPC, linear programs (LP), and even real-time optimization (RTO) are used. I know of one refinery where all control systems were moved from PID to MPC because of the in-house MPC expertise. I have used MPC with success but have returned to PID because existing and new PID features can be used in more innovative ways than expected to meet process objectives. I have to acknowledge I am the product of Shinskey’s books (download Appendix B). I like to tackle the process on a unit operation basis.

Concept: Loop coordination objectives are used to ensure nearly identical SP responses and to decrease loop interactions. A primary optimization objective is to achieve a more efficient or productive operating point without upsetting the process. The effective use of key PID features can achieve these objectives.

Details: There are three major loop coordination objectives plus an optimization objective. The first coordination objective is to ensure the simultaneous response of flow inputs to a unit operation (e.g., ratio flow control and blending). The second is to all secondary loops to have a uniform desired secondary PV response to a setpoint change in cascade control or model predictive control (MPC). This secondary PV response consistency is particularly important for parallel unit operations, so that differences in the primary controller tuning and MPC model are indicative of discrepancies in identical unit operations. The third coordination objective is to slow down the transfer of variability from the PV to the PID output to reduce interactions.

Coordination has traditionally been achieved by increasing reset time and decreasing gain. However, this tuning sacrifices disturbance rejection and rise time (Tip #71). Optimization has been traditionally achieved by integral-only valve position controllers that are difficult to tune. Today, there are key PID features (e.g., external-reset feedback) to provide an easier and more effective means of coordination and optimization. Use external-reset feedback with directional setpoint rate limits or a setpoint filter to provide the desired speed of response with disturbance tuning. For optimization loops, use a slow setpoint rate limit to provide a gradual approach to the optimum and a fast setpoint rate limit to provide fast correction for disturbances and abnormal operation. For surge loops, use directional rate limits for the analog output setpoint to provide a fast opening and slow closing surge valve. For valve position controllers that maximize coolant temperature setpoints or reactor feed setpoints to push coolant valves to the largest safe throttle position, use slow increasing rate limits and fast decreasing rate limits on the process controller setpoint being maximized (Tip #97). 


Watch-Outs: Setpoint rate limits on analog outputs (AO) will confuse maintenance and operations when they are manually stroking a valve. AO setpoint rate limits should be turned off when in manual. Controllers without the positive feedback implementation of integral action may not have external-reset feedback.

Exceptions: Optimization must take a back seat to the correction of large, fast disturbances. To prevent equipment damage and an environmental violation, an open loop back up may be needed (Tip #91).

Insight: The response of control loops or final control elements can be coordinated to work together to meet process objectives by the use of setpoint filters and velocity limits and external-reset feedback.

Rule of Thumb: Set a setpoint filter time that the slowest coordinated loop can achieve, slow down the AO or PID setpoint rate limit in both directions to minimize interaction, and set the AO or PID setpoint rate limit slow in the optimization direction and fast in the protection direction.


About the Author

Hunter Vegas, P.E., has worked as an instrument engineer, production engineer, instrumentation group leader, principal automation engineer, and unit production manager. In 2001, he entered the systems integration industry and is currently working for Wunderlich-Malec as an engineering project manager in Kernersville, N.C. Hunter has executed thousands of 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. Hunter earned a B.S.E.E. degree from Tulane University and an M.B.A. from Wake Forest University.



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.


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

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