Ask the Automation Pros: What Topics Should Be Covered in an Undergraduate Process Control Course?

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 solicit responses from automation professionals. Past Q&A videos are available on the ISA YouTube channel; you can view the playlist here. You can read posts from this series here.

Russ Rhinehart's Question

What topics should be covered in an undergraduate first course on process control, particularly in chemical engineering, but possibly also in mechanical and electrical engineering?

In a one-semester course, there are about 35 50-min MWF periods for substantive lectures. Although a semester might have more than 16 weeks, when one subtracts finals week, spring break, holidays and snow days, in-class testing and reviews, there are only about 30 hours of contact time. Some topics could require three or more lecture sessions. So, perhaps there could be 15 separate topics introduced into a course.
These 15 topics might represent only 5% of what the control engineer needs to know. The engineer must self-learn the other 95%.
About 80% of BS graduates start industry careers, so a course should prepare students for the practice. However, many textbooks seem to focus on the glorious mathematics of control (for instance, solving differential equations by inverting LaPlace transforms and using the method of partial fractions), which practicing engineers don’t do. Textbook authors should provide practice-relevant material. Although this includes foundational mathematical analysis, that should not be the course focus. We need to prepare students to enter the practice, where the K.I.S.S. principle rules and purchased software does the calculations, which is different from preparing them for graduate studies, where mathematical skill is a priority and writing code is required to do the calculations.
Many instructors of the control course have no control experience, which means they teach what is in the textbook they select, which is selected by academic values. If a professor is doing control research, then the course would be strongly shaped by that. We need texts that cover key topics, and provide practical exercises to help students understand and appreciate control concepts. These resources should also equip students with fundamental skills so they can independently learn the remaining 95% of control topics necessary for a successful career.
Control engineers don’t derive LaPlace transforms to describe process dynamics or to design control algorithms. They specify and calibrate measurement and transmission devices, choose filters, design advanced regulatory control strategies to solve specific issues (cascade, override, ratio, feedforward), design safety instrumented systems, design communication systems, trouble shoot and improve, reduce utility consumption, reduce variance, program computers (HMI, control structures, sequencing, data analysis, alarms) and more. The course should prepare students for all this.

I think the answer to “What topics should be in a first course in process control?” should start with practitioners listing the most important concepts, technologies and abilities they need. Then the course should be designed to equip the student with the concepts and fundamentals that enable students to self-learn the practice 95%. I think guidance needs to come from practitioners, not academics, on what book to use in developing materials — and instructors — that is aligned with the needs of most students.

Much of what is needed to be learned and motivation is in the January 2026 “Ask the Automation Pros: What Are the Prospects for an Autonomous Process Manufacturing Unit?” and the May 2025 “Ask the Automation Pros: Past and Future of Process Control.”

Robert Heider’s Response

If I were to teach again, I would use this book, cover almost all of it:

Basic and Advanced Regulatory Control System Design and Application
3nd Edition, (I used 2ed)
By Harold L. Wade

Harold also has a PC based lab, which I used in addition to my DeltaV lab. That lab was on the servers and I could use it for homework.

The book covers almost all they would need to understand control, mark-up P&IDs for projects and understand what to measure and where the valve should be piped. Covers all basic control techniques. I referenced it in my lab class for each appropriate experiment.

I also would cover batch control using ISA-88 standard, which I did. I had all four groups control the same batch tank, each performing a separate phase, so they all had to work together.

Patrick Dixon’s Response

In 2020, Miami University created a training program for students entering internships in automation. The program is called Systems Automation Springboard to Internships, referred to as SASI (https://miamioh.edu/cec/student-resources/sasi.html). This three-week crash course is an introduction in fundamentals over 120 hours of class and lab work. It is not intended to produce automation experts; the intent is to introduce concepts and terminology so that students hit the ground running when they begin their internship. By all measures, it has been an outstanding success.

I created the syllabus and segregated the technical material into four categories:

Math: The basics of control theory and proportional integral derivative (PID) need to be understand for anyone practicing process control. Most students are sophomores or juniors and have had calculus and perhaps differential equations, so PID can be explained. We say that LaPlace transforms are not a requirement unless the student wants to be able to read control theory. For most practicing engineers, LaPlace is not a requirement. We also introduce the concepts of deadtime compensation, multivariable predictive control (MPC), prediction models, neural networks and optimization. Again, this is introductory, so we do not try to make students experts on the material. We want them to be aware of what is mathematically possible in industry.

Electrical: Any practicing automation engineer at some point will have to troubleshoot, and without a fundamental understanding of electrical principles, this would be practically impossible. Sometimes you need to use the multimeter to confirm whether you have signals and whether the signals are right. Most students have been exposed to Kirchoff and Ohm in physics class, so that application in automation for troubleshooting is helpful. We do not cover power.

Instruments: It is important for students to know there are different ways of measurement and actuation. We cover the different ways a property such as flow can be measured and why a particular approach would be better for a chosen application. We also cover different valves and their characteristics.

Computer: This tends to be where 90% of the young automation engineer spend their time. Programming control logic and HMI tends to be the first work a student would get involved with. Some programming fundamentals are covered and students get their hands on PLC and DCS programming. Increasingly, computer networking, data communication and cybersecurity have become priorities for automation engineers. Software testing is also an important topic for any automation project. A broad introduction of computer skills helps prepare students for the nature of work in their internship.

On the final day of SASI, I cover some additional management topics that include project management, specifications and proposals, change management and background on industry experiences. These automation engineers may become leaders, and it is helpful for students to know what skills may be required later in their automation career.

In conclusion, a one-semester undergraduate class in process control should recognize that you can’t produce an expert automation engineer. The goal should be to introduce concepts and terminology in a compelling way to bring more talent into industry by showing them all the potential in the automation industry. The SASI syllabus achieves this goal.

Russ Rhinehart’s Response

SASI is a very impressive industry/academic collaboration. And I think Patrick Dixon’s categorization and list of topics for their syllabus are well-crafted.

George Buckbee’s Response

A few years back, Joe Alford and I wrote an article for Chemical Engineering Progress December 2020, “Industrial Process Control Systems: A New Approach to Educations,” addressing this topic. The article goes into some depth critical issues and highlights the use of ISA standards.

Michael Taube’s Response

I fully agree with your position, Pat, regarding the constraints of engineering education. My coauthor, Brent Young, who was the University of Auckland chemical and materials engineering department head at the time, had the same response when I conveyed a comment from an engineering supervisor with whom I was working when the supervisor complained about a lack of process safety understanding in recent grads: It’s simply not possible to add to the current curriculum. The crux of the matter is that, while hundreds of man-years of hard-earned practical knowledge and experience can’t be imbued into young skulls full of mush in a one-semester course (or even a four- or five-year engineering program), the content of the existing curriculum can and should be modified or enhanced such that students see how control and instrumentation affects the intended outcomes and behaviors of the other subject areas. This is what’s missing from current process control education: How it affects and ties in with the reality of process/equipment design, safety and operations!

Where I disagree with you is “They will be immersed when they are in industry.” In short, they won’t: The inexorable effects of “do more with less” has decimated staffing levels — including the loss of mentors — and most especially budgets for training and development. I was very blessed in that there was still some inkling of belief in (and budget for) staff development and training in the early part of my career. Thus, I was able to receive training in practical process control which overcame the dismal coursework I suffered through in school. Sadly, that policy has been removed by the “more bad advice” philosophies which have resulted in the unsustainable situation that now exists.

The recent arguments over the last two decades or so over who is responsible for engineer development and training — academia or industry — has the same outcome as a circular firing squad: Lots of blood and blame and no resolution. What is required is for enough people in both camps to care enough to push for change.

While I did pontificate quite strongly in the previous “Ask the Automation Pros: Past and Future of Process Control” about the fact that process control education needs to change, I didn’t address how. So here’s my input:

PID controls are extremely capable of addressing many different types of applications — refining/petrochem (process industries), robotics, electronics, etc. Thus, HOW it’s taught must be germane and relevant to the industry/discipline to which it’s being applied. Therefore, use appropriate textbooks and mathematical techniques: stay away from LaPlace transforms and frequency-based transfer functions unless they actually add value to understanding! (Usually they don’t add any value and merely confuse students and practitioners.)
As it pertains to the process industries, there are several aspects that must be addressed in undergraduate course(s) and may be split across multiple courses (i.e., process control, plant design, unit ops, distillation, etc.):
a. What is the difference between integrating processes (IP) and open-loop stable processes (OLS) – both mathematically and “graphically” (e.g., time-based response plots).
b. WHERE are these types of responses typically found (e.g., flows, temperatures, levels, pressures, etc.).
c. WHY is it that some process measurements (e.g., levels, pressures and temperatures) sometimes act as IP but in other cases like OLS.
d. How/why PID tuning differs for IP v. OLS.
Other detailed aspects to be addressed:
a. Mathematical/practical differences between positional v. velocity PID algorithms
b. Some historical and practical discussion on the development of PID, including the interactive form v. ideal form, parallel form, etc. and what having/using the different forms mean RE: tuning, especially when derivative is required.
c. The vital importance of back-initialization (i.e., “bumpless transfer”), which seems from my experience to be a lost concept, based on trouble-shooting and fixing control applications built by others.
d. Where/how override control is (should be) used for providing safety “backstops” for certain applications (e.g., hi/low pressure overrides for burner fuel gas flows), as well as for “advanced” regulatory controls (e.g., feed maximizer).
e. Where and how ratio control should be applied to address measured disturbances and understanding how differences in process dynamics (between the MV and feed forward variable [FFV] on the CV) affects ratio control’s response behavior.
f. The benefits, pitfalls and robust design requirements for using online analyzers for close-loop control, both GCs (asynchronous), as well as (FT)IR, UV, etc. (“continuous”), as well as how lab-based analysis can be used to “calibrate” or adjust online measurements (or even as a main control input).
In terms of defining manipulated variable to control variable pairing (“MV-CV pairing”), this is where process understanding comes into play and why chemical engineers need to have a better understanding of how to assess and then define possible MV-CV combinations, using a relative gain analysis (RGA) as one of the tools, both during greenfield design and brownfield enhancements/improvements.
How to analyze real plant data for assessing process behaviors (e.g., determining if it’s an IP v. OLS) from manual step tests and/or “opportunistic” events.
How to use dynamic process simulations to assess/design (advanced) regulatory controls, as well as to assess different mechanical designs (well BEFORE the mechanical design is completed/approved).
Understanding how to address nonlinear behavior from “simple” (i.e., valve characterization) to more complex (i.e., pH control).

A few years ago I developed a presentation on the “Eight Rules for Successful Controls Implementation.” Here’s the summary:

I. KNOW the process and how it’s operated
II. Understand the primary and ALL the secondary (and tertiary) control (operational) objectives
III. Understand (and USE) the control systems’ capabilities
IV. Clearly communicate controller functions to all stakeholders (ESPECIALLY the operators!)
V. Make it reliable and robust (i.e., the design and implementation).
VI. Tuning: Makes a good design into a great implementation
VII. Provide an intuitive interface for the operator
VIII. Document the design/implementation (DURING the design process) and publish follow-up activities and needs

Finally, all the above must be presented from the perspective of practical implementation, so having input from and references to books, articles, presentations, etc. from industry practitioners (i.e., Greg McMillan, Shinskey, etc.) is vital to successfully convey the practical application of process control principles to real-world processes.

Russ Rhinehart’s Response

Michael, great responses. Thanks.

As a note, I also think “bumpless transfer” is very important, but when I mention it in papers I submit to academic journals, the reviewers dismiss it as irrelevant and want it removed from the paper. I think it is because they don’t understand the concept or the problem with MAN to AUTO transfer, but they are in control, the gatekeepers of academic journal articles and do not understand the reality of control. And they write the textbooks!

I taught fluid mechanics, heat transfer, computer programming and ChE process design. To me, the texts for those courses balanced both theory and application. But process control texts do not.

Somehow, we need to get authors to accept what should be in the process control texts, and somehow, we need to get instructors of the undergraduate control course to accept practice-oriented texts rather than graduate theory-oriented texts.

Michael Taube’s Response

Thanks for the feedback and confirmation, Russ.

Even though I wasn’t plugged into the academic world while I was in university (c. 1980s), it was clear that the senior professors all had a deep respect and understanding of the “real world” and the importance of conveying how the theory applied to it. Sadly, since then (as you confirm), academics — for the most part — just don’t get it! Perhaps this is why I so enjoyed working with my late friend, colleague and coauthor Dr. Isuru Udugama. He was very curious about how things really worked and had a great desire to engage in research that could actually work, in spite of having a PhD! 😃

Academia’s neglect of the real world and the collateral effect on process control education is also why I have such a passion for communicating the importance of process control and instrumentation: It comprises a very small part of all process plants, but exerts great leverage and effect on their safe and profitable operations. My passion has also been greatly renewed since being asked to be part of the Texas A&M University Instrumentation & Automation Symposium Program Committee, and why I’ve reached out to my network of contacts, including this learned group, to participate. While there are other conferences that touch on or have a tacit focus on instrumentation and control (I&C), the A&M Symposium was founded with the explicit purpose of educating (chemical) engineers about I&C and its proper design and implementation, and for industry and academia to share success stories and lessons learned. I am working to return the Symposium back to that purpose.

Peter Morgan’s Response

Thank you, Russ, for making mention of the importance of ”bumpless transfer” which is seldom referenced in undergraduate texts. For simple loops even cascade loops or loops incorporating feedforward, the modern DCS typically incorporates provisions to ensure bumpless transfer from manual to auto (or manual to cascade), this most often through the configured association of regulatory type functions. The same cannot be said (with certainty) for loops configured in a PLC and for loops of greater complexity, e.g., loops employing cross limits or algebraic (non-initializable) functions. Although special provisions for bumpless transfer are easily incorporated, if the vendor supplied provisions are not understood and required special provisions are not configured, the consequences can be, in the least case surprising, and the worst case damaging. Incidentally, as just mentioned, while configuring logic to ensure bumbles transfer a classic PID controller is not complicated, when integral action is implemented using filtered positive feedback, additional logic is ordinarily not required.

To aid in the understanding of the principles of closed loop control and the utility of the PID controller, I would recommend that courses include an introduction to the LaPlace transform, and its frequency domain equivalent. After all, if it weren’t for the phase shift occurring over elements of the control loop, our job as control engineers would be far less interesting (and less challenging) than it is.

In control loop tuning, that the integral term of can be set to match the dominant time constant of the process to result in cancellation of the dominant pole is one of the characteristics that simplifies the tuning of the PID controller and has favored it use for so long. Understanding too, that the PID controller also introduces phase shift (easily calculated for a given frequency from the LaPlace transform for the controller), that can ultimately (in the extreme) change the thoughtfully configured negative feedback to positive feedback with “exciting” consequences, gives insight on observed behaviors and guidance on remedies.

I have to admit that there is a common aversion to LaPlace transforms, most likely due to their introduction without apparent purpose except to try the endurance of students. By reference to first principles differential equations for simple or simplified physical kinetic processes, the LaPlace transform and equivalent gain and phase output/input relationship can be defined with a new relevance to budding control engineers, especially when the same treatment is applied to the PID control algorithm. The use of spread sheets or Visual Basic programs and the like, can engage students in exploring the frequency response for various processes; for example first, second order, first order with dead time to illustrate the conditions that give rise to instability and the basis of the Nyquist tuning method (just one of many).

I would suggest that elements of ISA’s Technical Report TR 5.9 2023 “Proportional-Integral-Derivative (PID)” written by a number of contributors to “ISA Ask the Pros,” could be put to good purpose in developing any introductory course on process control as well as encouraging further study.

Patrick Dixon’s Response

I have already submitted my comments for the column, but I want to offer an opinion.

As chair of an academic committee at Miami University, we commonly get recommendations on adding more content to curriculum. Sometimes these suggestions seem to assume the academic course load is infinite. Our committee will always push back when the credit hours inflate to an unreasonable burden on students.

Our committee always keeps in mind that our recommendations are to prepare students for careers, but not to produce experts. They don’t need to graduate with everything in their head that we have. They need fundamentals that will enable them to understand what they are introduced to and become future experts. Whether it is ladder logic, Python scripts in an HMI, valve specifications, MPC, data analytics or project management, the exposure in college will be shallow but they will be immersed when they are in industry. There are many careers paths in automation. Our goal with SASI is to paint a picture of what is possible. When students matriculate, they will find their calling and dive deeper into the pertinent subject matter.

Lucinda Weaver’s Response

Wow! Does this topic ever hit home with me. The instrument class (winter term, junior year) was fairly easy. We learned about the types of instruments in general, but nothing very specific because “technology was changing so fast that by the time we graduated, what we had learned was obsolete.” The controls class that followed then next term was the class that I thought was going to cost me a fifth year in college because it was a pre-requisite for design class senior year. The stupid LaPlace transformations about killed me. However, somehow as usual, I gutted it out and got my passing C and finished on time. Given that experience, how ironic was it that I would spend the next 45 years in instrumentation and controls?

So, what should be taught in college instrument and controls classes? I think the types of instruments are fine, learn what technologies are available are the advantages and disadvantages of each type. Simple stuff — RTDs are great for most temperature applications and are much easier to install/set up; however, if you are working on things that are very high temperature you need to go back to old fashion thermocouples with that nasty expansion wire. (Put the transmitter in the head in that case; skip the extension wire.) A lot of general knowledge of instruments can be taught at this time and still be useful two years later.

Here I am going to diverge from others. Learning some control theory as others tell you is great; understand how a PID loop works. However, skip all that math stuff about loop tuning. If you go to work in a refinery or another organization that does mostly continuous control, they will have their own methods for teaching loop tuning. If like me, you go into the batch control business, you will get to tune a loop occasionally when you wind up with a solvent or waste water recovery column.

So what do students need to know? Key performance indicators. Yup, those nasty KPIs. They will also need safety requirements as well. Give students a process flow diagram for a unit operation providing the material and energy balances. Provide them with the key performance and safety requirements. Teach them to turn that into a P&ID with an outline of how the unit would have to be controlled to meet the KPI and safety requirements. When they are done on their own, put them together in teams and do the same thing where they all have to agree on a method. This is how I worked with my interns and co-ops. No, I did not make them do the exercise on their own, I usually started them out in the field filling out the IQ forms to confirms the instruments installed were those that were specified. They needed to know what instruments looked like before they got to the P&ID part. But they always participated in P&ID development meetings where we added all the instruments to the PFD and that did more than anything for them to understand about controls. No instrument to provide data, no valve/pump/etc. to start and stop flows, no control. Then I sent them back to college and told them that all the control stuff they learned.

Russ Rhinehart’s Response

Topics for a First Process Control ChE Course

It seems to me that practitioners have continually complained that the texts for the first course in process control are substantially under preparing students for the practice. I agree. It seems there is too much focus on mathematics representing analog feedback control of disturbance free, noiseless, linear and continuous operations. And too much focus on mathematical theory such as proofs of the final value theorem and how the limit of N lags leads to pure deadtime.

If practice issues are omitted, the focus of the textbook is appropriate for an engineering science degree. If the math/science is missing, the focus is for an engineering technology degree. An engineering degree requires both math/science and practice context. It needs to generate workforce-ready graduates who can also legitimately learn (understand the fundamentals) of the rest of what they need to know.

For practitioner affirmation, the topics in the book need to have practitioner relevance. For academic acceptance, the book needs to have math/science fundamentals. A first course in process control should contain both.

I appreciate the answers from the other experts in the Ask-the-Pros community. And considering the number of topics in the “Automation Body of Knowledge,” it would not be possible for one course to cover all. The one course should provide a broad understanding of the whole and include the key mathematical procedures.

Here is my opinion on what the course should contain:

A PFD is essential to identify the process objectives and disruptions. But it needs to be converted to a P&ID. There are several stages: First, choose primitive control loops, and decide whether PID is justified or PI, and which sensors and where they are to be located and FC or FO and RA or DA. Then decide where cascade or ratio will improve the loop. Then whether feedforward or decoupler strategies are warranted. Then add secondary control loops such as level control, pressure control, etc. to the developing P&ID. Then consider where safety overrides are needed (such as preventing over-heating or vacuum) and how override control is structured (PI or triggers) and reset feedback is justified. I think each stage of developing a P&ID needs to come after the presentation of each regulatory topic.
We design and communicate control systems with P&IDs. So, ISA Standard 5.1 on symbology should be a fundamental part of the course. Block diagrams, also. for analysis of loops.
Control reduces waste and improves quality, which translates to higher throughputs and/or lower cost of raw material and utilities. So, I think essential topics in a control course should be related to how control decreases variance (propagation of variance), and how this can be converted to improved profitability (operating closer to constraints or specifications). So, several profitability metrics need to be part of the course. Variation may not be Gaussian (normal), so this treatment should include non-Gaussian propagation. I think simulations with phenomenological models provide a much more credible prediction of variance and variance reduction than analytical methods, but I’d like to ground the propagation of variance in classical statistical methods.
Control improves safety and equipment life (part of loss prevention). So, I think essential topics in a control course should be related to how these lead improvements to lower operational costs. Safety includes probability of events, which includes AND/OR/Not logic and calculation of the probability/frequency of compound events.
Control communication systems use scaled signals, which are additive (for inventory) and divided (for ratio). If tank A is 50% full sending a 12mA signal but 3 times larger than tank B which is 75% full sending a 16 mA signal, is the cumulative inventory 12+16=28mA or 50+75=120%? I think essential topics in a course should include scaled signal calculations.
I think students should be able to specify orifices and valves to meet rangeability, sensitivity, linearization, delay, lag, cavitation and low cost criteria. And how they increase pressure requirements on pumps. And the impact of valve and pump characteristics on process gain and pressure losses. Lots of fundamental process equations here.
All elements that are needed for control should be sized x% larger to be able to accelerate transitions to new set points, new flow rates. For instance, a heat exchanger may need to be 20% larger than indicated by the PFD steady state calculation. Dynamic modeling can reveal the excess power required to desirably accelerate the process to the setpoint.
Students need to understand the why of filtering and external reset feedback and the role of P, I & D, and the many options for the PID controller. I think both the calculus and digital math need to be included, so engineers can understand the code. And also the LaPlace notation which 1) remains the language for communication, 2) shows how FF and erf and derivative filters work and 3) so inventive engineers understand that their innovative code is just proportional on the filtered projected actuating error. LaPlace mathematics and block diagram representations should be included.
Metrics for goodness of control. Focus on regulatory not setpoint response. Include both MV and CV behaviors.
Heuristic methods for on-line tuning of controllers should be a course topic. No one uses the ultimate method. And the safer but time-consuming reaction curve method to generate FOPDT models for tuning rules seem to always require heuristic fine tuning. Might as well as teach heuristic tuning methods instead. And gain scheduling is important.
Although FOPDT models are our way of communicating dynamics, gain scheduling and setting up FF, the reaction curve method (from the pre-computer age) is time-consuming and upsets the process. Teach 1) the skyline input and computer regression empirical method, 2) how to generate FOPDT models from first-principle process models and 3) how to use first-principle models to gain schedule FOPDT coefficients.
Generate dynamic models of unit operations from first-principle modeling. This leads to nonlinear ODEs, numerical solutions and coding.
Startup, shutdown and batch sequencing are very important for safety, and batch fill metering is very important for quality. Standards guide step procedures. And process design and device mechanics are critical for precision.
Standards, especially ISA 5.1 (Symbology).
Human interface design for rapid and complete interpretability of the control system. Understand the concepts and color codes.
Balance of perfection with sufficiency, complexity with simplicity and how to satisfy operators and managers (your customers who are not control experts).
Statistical process control tempers managerial over-control and leads to rational process improvement, which reduces variance, which translates to higher throughput or lower costs. The statistics part is relatively simple. Include it.
Set point optimization to shape yield, lower costs or increase throughput. Include some multi-variable optimization.
Include device calibration. One point, two point, piecewise linear and the impact on measurement precision throughout the range.
Include resolution from digital truncation anywhere in the instrument system and the impact on nonlinear functions. Add stiction.
After PID feedback introduce advanced regulatory topics — cascade, ratio, tempering loop interaction (loop paring, detuning, one-way static decoupler, …), override and erf, feedforward and output characterization.
The future? I think it might include the use of first-principles models in feedback control.

The math techniques of this set of topics should please academic sensibilities.
• ODE generation
• Calculus and numerical solution
• Dynamic simulation
• LaPlace notation of linear models
• LaPlace analysis of loops
• Propagation of variance
• Probability of compound events from frequency data
• Statistical patterns
• Optimization
• Scaled signal analysis (linear translations and conversions)
• Digital signal discretization and resolution
• Regression
• Piecewise linear modeling
• Simulation

Resources which should be available to the students include: Relevant standards, Liptak’s I&CE’s Handbook, ISA Guide to the Automation Body of Knowledge Fourth Edition, Miller’s Flow Measurement Engineer’s Handbook, Perry’s ChE Handbook, McMillan’s Process/Industrial Instruments and Controls Handbook Sixth Edition, AT&T and John Oakland’s SPC book, ASTM Manual on Presentation of Data and Control Chart Analysis, …

Mike LaRocca’s Response

I love this topic and I wish I had more time available to collect my thoughts and add to the conversation greatly. I have only a few random comments to offer. If there is anything in my below list that I think is worth emphasizing, it is item 4.

I had only one controls theory class as a ChemE student. It was highly math focused (transfer functions, LaPlace transforms, Bode and Nyquist plots, frequency response), and while I enjoyed doing the math, I found myself wondering what it would be used for. The chief cause of that wondering was that I did not have the foggiest notion of what a “controller” was physically throughout the class; I didn’t have a clue about how process measurements like temperature and pressure were obtained or the equipment used; I did not have a clue how a control valve worked. I never saw any of those things in action. I never held any of them in my hands, or even saw a picture of one throughout that class. I did not have any idea how I might apply all that math and those plots or what they were really used for other than math exercises. It would have been vastly helpful to have seen something; to have seen an application or use. I came out of the class thinking — well, that doesn’t look like anything I’ll be using in my life. It wasn’t until I started working in a chemical plant that application understanding began to take shape in my brain. Once I saw things in action and understood the practical applications of controls, I found myself drawn to it because of what I saw as one of the biggest levers for making chemical processes work like you want them to. It quickly became the thing I wanted to learn more about.
I’ll note that while I have focused on the application of controls and automation throughout my engineering career, I have never once have had the need to apply LaPlace transform or create a Bode plot.
I think Patrick’s syllabus is great. It has great practicality. However, I know many engineering universities frown on teaching practical skills. Their stand is that they should teach theory and fundamentals, and let the student gain practical knowledge/skills on their own. There is a balance that should be applied I think for each aspect of the engineering curriculum, and from my standpoint, controls and automation is one area where the balance should lean toward the practical rather than the theoretical, since most engineers are unlikely to be dealing with fundamental theory when it comes to controls.
When I look at Patrick’s syllabus, it occurs to me that much of it might be best covered in a controls lab environment. I think a little bit of control theory followed by hands on experience in a controls lab dealing with transmitters, DCSs, PLCs, control valves, etc. would be ideal. From my observations, most controls labs consist of playing with a PID emulator on a computer, and playing around with tuning parameters. I think a lab with a small DCS or PLC wired to transmitters and valves and that has connections to a dynamic process simulation system would be the absolute idea. Lab exercises that demonstrate how all that equipment works together and that illustrates commonly encountered control situations and problems would be most instructive.
If there is one certainty I’ve observed about controls and automation in my career, it is that only the people who do it have a great appreciation for it. I would say few managers understand its value, and how important it is to do it well. They also have little understanding of what is needed to do it well. Many times, controls are not even thought about until the end of a process design, and then it often becomes too late or too high a cost to implement them well. I can say the same for many university professors in terms of their appreciation level. I think recent engineering graduates armed with better experience and knowledge could help raise the strategic business value of well-designed controls and automation systems in management’s consciousness.
I have spoken to several college classes over the years about chemical engineering careers, and I always mention that I think control engineering is one they should investigate. Many students give a somewhat blank stare when I mention it because they don’t really know what it is much as was the case with me when I was their age. We know we have a shortage of controls and instrumentation people in industry. I think it would go a long way to getting more students interested in it, and as a result, get more talented people into the field, if universities did a better job of teaching it and making students aware of the tremendous value and opportunities it offers.

Greg McMillan’s Response

I think good resources would be the 2026 ISA-Wiley A Guide to the Automation Body of Knowledge, Fourth Edition and the 2019 McGraw-Hill Process/Industrial Instruments and Controls Handbook, Sixth Edition, edited by me and Hunter Vegas, that has sections written by many of the Automation Pros and other process automation experts with a concise list of best practices at the end of each section. I also suggest the November 2020 Control Talk Column with Russ Rhinehart, “The real deal with control education.”

I also advocate the use of ISA standards and technical reports as resources, particularly ISA-5.1-2024, ISA-TR75.25.02-2024 Annex A and ISA-TR5.9-2023. These resources have sections written by Automation Pros James Beall, Mark Darby, Brain Hrankowsky, Peter Morgan, Sigifredo Nino, Mark Nixon, Russ Rhinehart, Michel Ruel, Nick Sands, Hector Torres, Hunter Vegas and me. As a supplemental resource for those more interested in effects on PID performance detailed analysis, I can make my Momentum Press 2015 book Tuning and Control Loop Performance, Fourth Edition freely available.

I suggest the following topics be concisely covered in one day lectures: process relationships and dynamics, measurement performance and dynamics, control valve and variable frequency drive performance and dynamics, control strategies, data analytics, performance metrics, batch control, PID basic control algorithms and performance (single loop and cascade control), PID advanced control (2 days to cover feedforward, decoupling, dead time compensation and override control), the controversial topic of PID tuning and finally model predictive control. A digital twin and dynamic simulations are used for labs. A digital twin using DeltaV SimulatePro, HYSYSPlant and Matlab was setup by me at Washington University and was used by me and when I moved to Texas by Terry Tolliver as adjunct professors from 2002 to 2006 to teach a chemical engineering course on process control. When Terry was replaced by a direct hire from another university, the labs and course were scrapped and retreated to a traditional academic control theory course.

In 2010 to 2011 I did a dozen one-hour seminars and demos (Deminars) using DeltaV Simulate and MiMiC that were recorded by Jim Cahill. The labs covered a lot on advances in PID control.
https://www.emersonautomationexperts.com/?s=deminar

I did a December 2015 Control Talk Column with Mark Darby, “Universities role in revitalizing our profession,” who was teaching a University of Houston course on the importance of understanding the source of process dynamics and the progression to model predictive control.

In 2016, I helped develop DeltaV Simulate and MiMiC labs for the Missouri University of Science and Technology (Missouri S&T) for a chemical engineering undergraduate course on process control. I was also a guest lecturer for several weeks to help students learn about process dynamics and PID control capabilities. The professor hired did not understand or appreciate the significance of what I did, which was strange, since he came from a biotech company — until I learned he had little real hands-on experience with process control.

Russ Rhinehart’s Response

How to include practice related issues and exclude all but essential math in the process control course and get it accepted by instructors?

I’ve been seeking a solution for a long time. I think it is possible to strike this balance. I shaped my process control course to substantially follow Wade’s book, and supplemented the book with the math that supported the concepts. I used a lot of simulations, which I wrote in VBA that students ran in Excel. But how to shift the academic “way” and get a more practical and experiential course to become standard academic practice?

There are some industrial funded approaches. Sinclair supports process control at the U of Wyoming, Emerson supports it at Universidad Politécnica de Madrid, and SASI is a industry consortium practitioner instructed course and internship experience at Miami U of Ohio. If more companies feel the need to support workforce development they can make a change. At OK State U Celanese and ConocoPhillips have supported the process design course, by creating projects and providing feedback to students after their project presentations. There are many degrees of collaboration. In my experience, company partnership in education invokes strong allegiance to the company by students, which is a strong recruiting advantage.
AIChE and Dow have a partnership for a faculty Summer School for instructors teaching the design course. Most faculty have no industrial experience, and it is especially needed in the process design course. It is a 3, or so, day event that includes visits to plants and seminars on industrial practices and multi-objectives for process design. It is great. I believe the cost to the university is just to send faculty is travel. I believe that Dow picks up the tab for all other expenses. Presentation materials from the Summer School are used by faculty in their course, and faculty can relate their understanding to students. In my opinion, both faculty and students form an allegiance to Dow, which also benefits recruiting.
A book “Introduction to Process Control” could have chapters co-authored by industry and a professor. The practitioner could shape the contents and initial chapter presentation, and after establishing the need for the topic, the professor could provide the supporting math. I think such a book needs an editor that understands both the practice and academic environment to be able to direct the overall contents and keep a proper balance in each chapter. Academics publish research papers for free. I think that the book should be an e-version and given for free to anyone. The benefit to authors and their employers would be their visibility. An e-version could be easily edited to eliminate errors and add clarifying comments. It could be available on the ISA site or the American Automatic Control Council site or even multiple private sites such as those of the editor and authors. Along with the book should be simulators in several computing environments to make it easy for instructors and students to use. I think the ISA Academic Engagement Committee could have a sub-committee to develop the book. The editor or committee would need to manage updates and who gets to distribute it. Once there is a book, how can we get instructors to choose it? I think promoting the book would need articles from both faculty and practitioners promoting the concepts and utility of the book within the literature that academics read (such as AIChE and ASEE publications and conferences). I wonder what would be the push-back from the authors of the major texts who might see their sales of books drop?

Mark Darby’s Response

My suggestions are directed at the chemical engineering undergraduate course, which usually includes both dynamic modeling and control. If the course split is roughly 50-5 then, using Russ’s numbers, leaves at most 15 hours of actual classroom instruction for control topics. This limits the number and/or depth of the control topics.

For the control portion, I would prioritize the following:

• PID, feedforward, ratio, cascade and override.
• PID tuning of simulated and/or lab systems to get a “feel” for the effect of tuning parameters on closed-loop behavior. Addressing load and SP tuning (not or).
• As noted by others, distinguishing processes in terms of open-loop stable, integrating and unstable.
• The various components of a control loop, including instrumentation (typical measurements), AtoD and DtoA conversion and final control elements (especially valves). Include the use of scaled units.
• Safety, including and interlocks and Safety Instrumented Systems (SIS).
• First principle and empirical models (regressed from data). Inferentials models.
• Introduce feedback of model error vs. setpoint error.

Additional worthy topics:

• Process/loop interaction, RGA
• Frequency response (brief, include filtering)
• Addressing nonlinearities
• Typical unit controls (heat exchanger, furnace, compressor, distillation column)
• Model predictive control
• Optimization

Given the challenge of classroom time vs. topics, instructors can look for opportunities to incorporate selected topics suggested by this group. One example: highlight the following topics from the article by Joseph Alford and George Buckbee, some of which may not be covered in the typical course or textbook:

• Instruments and electronic communication
• Analytical systems
• Safety instrumented systems
• Software tools
• Abnormal situation management
• Manufacturing execution systems
• Documentation

Another thought is connecting bumpless transfer, anti-reset windup and overrides to the safety topic.

From my experience and in talking with universities, the dynamic modeling portion of the course is critical. Students may not have had sufficient previous exposure to dynamic balances. First principles knowledge is critical in process understanding as well as “building in” insights or known relationships into models used for control, which takes on increased importance with models developed with AI and machine learning. There is also the insights that can be gained from steady-state balances (dropping the accumulation term), which include determining the theoretical process steady state, calculating process gains (and how they vary) and determining controlled variables.

I believe the LaPlace transform is the best method of solving ordinary differential equations analytically. In addition, control documentation and identification routines often refer to a LaPlace domain representation (e.g., first order, second order overdamped and underdamped). Knowledge of transfer functions is helpful for simpler or ideal processes. But the coverage of LaPlace transforms can be overdone. More complicated systems should instead be solved numerically or simulated using tools available today.

As others have mentioned, simulation-based and/or lab-based exercises are critically important for developing process control understanding. The IEEE Systems Society Technical Committee on Control Education recommends in a first control course: moving away from weeks of mathematical modeling to starting with simple, intuitive problems and promoting the use of accessible hardware and software to enable hands-on learning. Actual examples:

• Including labs in every homework assignment.
• Use of Python, for example, to solve and simulate differential equations.

As also mentioned by others, there is only so much that can be included in the first process control course. Additional topics could be included in an elective course. Other topics mentioned in this post make for a good check list of what an engineer interested in control should learn. It could also serve as a checklist of necessary process control skills for companies that do not have a strong internal group.

As far as getting more industry knowledge in the classroom, I know some universities have brought in a lecturer or have hired a professor (Professor of Practice) with significant industry experience to teach the process control course. One thing that can easily be done is to bring in a process control practitioner to give a lecture or seminar.

Ed Farmer’s Response

The following may be a bit more acceptable to introduce process understanding to undergraduates:

Operations Understanding

In computer programming, there is an old and oft-used simple paradigm for organizing a computer program. It’s called “input, process, output.” This might be the entire description of a small, simple program but the principle expands naturally in large complex ones by repeating it for the various segments.

Process control engineers can use this simple approach for diagnosing processes and implementing suitable control strategies. By definition, a process starts with raw materials, manipulates them suitably and produces a desired output. Sometimes that’s as easy as turning a faucet handle to produce a flow of water.

Sometimes it involves something a bit more complex, such as producing gasoline from crude oil. Sure, the input is crude oil and an output is gasoline but that happens step-by-step; ranging from preparation, followed by a series of steps, each producing a product and feedstock for the next.

Each of those steps has to be controlled properly to get the desired product out while transferring whatever’s left to the “input” of the next step in the overall process… and so on. Each of those steps begins with input from the previous one, converts that input to another product and outputs whatever’s left to the next step in the apparatus.

There’s a lot of instrumentation and control equipment involved in the overall process and each of the steps within. Understanding it requires understanding the “big picture” and the function of its individual steps. It’s easier to think through situations and problems by starting with the big picture. It’s usually in the form of a process diagram. If the focus is on control issues, it’s useful to begin with a P&ID — a process and instrumentation diagram that documents both the “big” and “small” issues.

With modern control systems there are often features that help one find their way — such as data collection and analysis tools. This often makes it possible for an astute engineer, operator or technician to sort out “what’s wrong in there” and launch the effort to “restore normal.”

All this is useful and understandable by competent people, and can reduce the seeming complexity to an obviously defective item in an understandable control loop. Being “competent” can usually be developed with the appropriate control systems training coupled with the basic “local” training relevant to the particular equipment. Fixing something involves finding the process involved, checking its input and evaluating its output.

In new ventures, one usually needs a step back to improve overall visibility, sort out what it is and how it works. Start with the highest level input, find the output(s), and sort out what happens in the “process” involved between. Expand the search by module until the big picture emerges.

Getting into such issues is an activity in a field called “operations research.” It was developed initially by the British Army during the Crimean War. Its purpose was to determine and refine the issues and actions required for success in military operations. The methodology and motivations applied well to many other activities including development and understanding of industrial processes. The prime publication is a book, currently in its 11th edition, by Hillier and Lieberman, called Introduction to Operations Research. Over its 28 chapters, it gets deeply into “how things work.” It promotes a lot of thinking and illustrates a lot of methodology over many situations. It’s easy to think of it as highly relevant to control engineering, but when applied to what should be involved in engineering education, it’s a bit broad and diverse. Getting and understanding the core ideas, though, would certainly make a couple of good weeks in a more general course.

When I was in my EE program, our lead professor spent his summers consulting in some development-focused industrial work. He introduced us to the relevant thinking about these things with pertinent examples from his summer work — with his emphasis on thinking things logically through. I can still vividly remember him starting an explanation of a small problem with, “Let’s take a deep breath and a quick view from the beginning....” Sometimes the quick view took the rest of the lecture and a homework problem, but as we came to understand the purpose, it became easier and faster.

About the Authors

Russell Rhinehart has experience in both the process industry (13 years) and academe (31 years). He is a fellow of ISA and AIChE, and a CONTROL Automation Hall of Fame inductee. He served as president of the American Automatic Control Council and editor-in-chief of ISA Transactions. Now “retired,” Russ is working to disseminate engineering techniques with his website (www.r3eda.com), short courses, books and monthly articles. His 1968 B.S. in ChE and M.S. in NucE are both from the U of Maryland. His 1985 Ph.D. in ChE is from North Carolina State U.

Bob Heider has over 50 years as a process control engineer with an emphasis on the design of advanced process controls and process development. He spent 33 years with Monsanto in various plant and corporate engineering roles and worked with Greg on first PROVOX system installation.

Bob has 16 years as an adjunct professor at Washington University's department of chemical engineering.

Professor of Digital Process Control Laboratory, using DeltaV/Fieldbus control system; Unit operations class and laboratory.
Secured grant for research at the National Corn to Ethanol pilot plant, Southern Illinois University, Edwardsville, IL, to develop inferential control models of the process.
Research engineer at the Modeling, Analysis and Process Control Laboratory for Electrochemical Systems (MAPLE) Lab, wrote Li battery simulation programs, supported research effort.

Bob also worked for five years at Confluence Solar, providing control expertise to support the company mission to develop premium quality single crystal silicon substrates for solar applications. Presently, he is an independent engineering consultant for various confidential clients. He is a Fellow of the International Society of Automation.

Peter Morgan is an ISA senior member with more than 40 years of experience designing and commissioning control systems for the power and process industries. He was a contributing member of the ISA 5.9 PID committee for which he won the ISA Standards Achievement Award and has had a number of feature articles published in Control magazine.

Pat Dixon, PE, PMP is president of www.DPAS-INC.com, a system integrator with expertise in data analytics and advanced control. Pat has experience in industrial automation beginning in 1984, having worked for SD Warren Paper, Honeywell, Pavilion Technologies, DuPont and Emerson as well as system integrators. Pat is a professional engineer in four states and a certified project manager. His LinkedIn profile is: https://www.linkedin.com/in/dixonpatrick/

George Buckbee is a P.E. and ISA fellow, and is now president of Sage Feedback LLC. With over 40 years of practical industry experience, George worked across many process industries all over the globe. Since the early 2000s, George was at the forefront of developing control loop performance monitoring and other software tools. The author of two books published by ISA and dozens of articles about process control, George is also a well-known instructor and presenter at conferences and in webinars. He holds a B.S. in chemical engineering from Washington University in St. Louis, and an M.S. in chemical engineering from the University of California at Santa Barbara.

Michael Taube is a principal consultant at S&D Consulting, Inc. Serving the greater process industries as an independent consultant since 2002, he pursues his passion to make things better than they were yesterday by identifying the problems no one else sees or is willing to admit to and willingly “gets his hands dirty” to solve the problems no one else can. Due to the continued occurrence of individual injuries and fatalities as well as large-scale industrial incidents, he collaborates with operational excellence and safety culture experts to promote a real and lasting cultural shift in the process industries to help make ZERO incidents a reality. He graduated from Texas A&M University in 1988 with a Bachelor of Science degree in chemical engineering. His LinkedIn profile is: https://www.linkedin.com/in/michaeltaube/

Lucinda Weaver has worked on capital projects for over 45 years. She started as a programmer doing batch control on the Fisher DC2 and the last 10 years of her career she has been a project technical lead supporting of instruments, controls and everything else with a wire attached to it. Projects have been mostly pharmaceutical all over the US, Maritime Canada and some in Ireland. Retirement comes at the end of 2025 unless someone mentions the words "greenfield facility" and "Dublin, Ireland" in the same sentence; then she will reconsider. Lucinda is a proud Oregon State Chemical Engineer.

Mike LaRocca is a chemical engineer who has spent 45+ enjoyable years working at manufacturing sites in the industrial chemical and pharmaceutical industry. Early in his career he found he was drawn to and had a knack for process control and automation technology and process troubleshooting. He has held roles in project engineering, manufacturing, engineering technical services and E&I maintenance. Mike is an ISA St. Louis Section board member focused on student outreach and membership.

Gregory K. McMillan retired as a Senior Fellow from Solutia Inc. in 2002 and retired as a senior principal software engineer in Emerson Process Systems and Solutions simulation R&D in 2023. Greg is an ISA Fellow and the author of more than 200 articles and papers, 100 Q&A posts, 80 blogs, 200 columns and 20 books. He was one of the first inductees into the Control Global Process Automation Hall of Fame in 2001, and received the ISA Lifetime Achievement Award in 2010, ISA Mentor Award in 2020 and ISA Standards Achievement Award in 2023. His LinkedIn profile is: https://www.linkedin.com/in/greg-mcmillan-5b256514/

Mark Darby is an independent consultant with CMiD Solutions. He provides process control-related services to the petrochemical, refining and mid/upstream industries in the design and implementation of advanced regulatory and multivariable predictive controls. Mark is an ISA senior member. He served on the TR5.9 committee that produced the PID technical report and has presented at ISA technical conferences. Mark frequently publishes and presents on topics related to process control and real-time optimization. He is a contributing author to the McGraw-Hill Process/Industrial Instruments and Controls Handbook, Sixth Edition. His LinkedIn profile is: www.linkedin.com/in/mark-darby-5210921

Ed Farmer completed a BSEE and a Physics Master degree at California State University - Chico. He retired in 2018 after 50 years of electrical and control systems engineering. Much of his work involved oil industry automation projects around the world and application of the LeakNet pipeline leak detection and location system he patented. His publications include three ISA books, short courses, numerous periodical articles and blogs. He is an ISA Fellow and Mentor.

ISA Interchange

Ask the Automation Pros: What Topics Should Be Covered in an Undergraduate Process Control Course?

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Ask the Automation Pros: What Topics Should Be Covered in an Undergraduate Process Control Course?

Russ Rhinehart's Question

Robert Heider’s Response

Patrick Dixon’s Response

Russ Rhinehart’s Response

George Buckbee’s Response

Michael Taube’s Response

Russ Rhinehart’s Response

Michael Taube’s Response

Peter Morgan’s Response

Patrick Dixon’s Response

Lucinda Weaver’s Response

Russ Rhinehart’s Response

Topics for a First Process Control ChE Course

Mike LaRocca’s Response

Greg McMillan’s Response

Suggested Lecture and Digital Twin Lab Topics

Russ Rhinehart’s Response

Mark Darby’s Response

Ed Farmer’s Response

Operations Understanding

About the Authors

Greg McMillan

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ISA Interchange

Ask the Automation Pros: What Topics Should Be Covered in an Undergraduate Process Control Course?

Categories

Subscribe Here!

Ask the Automation Pros: What Topics Should Be Covered in an Undergraduate Process Control Course?

Russ Rhinehart's Question

Robert Heider’s Response

Patrick Dixon’s Response

Russ Rhinehart’s Response

George Buckbee’s Response

Michael Taube’s Response

Russ Rhinehart’s Response

Michael Taube’s Response

Peter Morgan’s Response

Patrick Dixon’s Response

Lucinda Weaver’s Response

Russ Rhinehart’s Response

Topics for a First Process Control ChE Course

Mike LaRocca’s Response

Greg McMillan’s Response

Suggested Lecture and Digital Twin Lab Topics

Russ Rhinehart’s Response

Mark Darby’s Response

Ed Farmer’s Response

Operations Understanding

About the Authors

Greg McMillan

Recent Posts

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Related Posts