AI In My PID Loops? It’s More Likely Than You’d Expect

April 7, 2025

Some wonder if AI will replace PID control loops. The reality is that, instead of replacing PID, AI is stepping in to help keep things running smoothly without upending regulatory trust. Think of AI as an extra set of eyes on your process data, nudging you in the right direction rather than taking over the controls.

Bill Mueller

I was nursing a lukewarm vending machine coffee recently when I overheard two fresh-faced engineers complaining about the PID tuning process and coming up with ways to tear down centuries of control theory with AI-powered alternatives.

Dubious. Extremely dubious.

This overheard conversation took me back to the first time I wrestled a PID loop into submission at three in the morning. Fluorescent lights flickered above stainless-steel cook kettles churning out binding syrup for diabetic protein bars. My eyes were glued to a jittery two-pen RS Logix 500 trend, mocking me with endless oscillations.

Then, seemingly out of nowhere, it produced a flawless control trace that neatly followed the stepped setpoints I’d chosen for my Ziegler-Nichols hand calculations.

Fast forward to today and its AI, machine learning and neural nets driving industrial technology conversations.

In GMP (Good Manufacturing Practices) life sciences, however, the primary focus is stability and traceability. That’s why replacing a control staple like the PID loop is going to be a steep hill to climb. The difficulty is not so much related to technology as it is to acceptable validation testing.

Think of it as a tireless apprentice, quietly sifting through temperature spikes, pH dips and feed-rate anomalies.

So, while some dread that a tentacled AI is threatening to supplant the PID loop, the real question is: How can AI bolster existing process control methods?

This where the AI digital sidekick comes into the picture. Essentially, this is advanced software that scours process data, spots trends and suggests actions. Think of it as a tireless apprentice, quietly sifting through temperature spikes, pH dips and feed-rate anomalies.

Instead of hijacking the process, it nudges you with suggestions like: “Hey, maybe dial down that integral gain.”

This is better than handing over full control to AI. That’s why my recommendation is to not rip out the proven PID loop but augment it with AI.

I say this because regulators still trust those three letters — P, I and D — as symbols of simplicity and safety. A tuning agent can crunch numbers in the background and offer adjustment recommendations, but the PID loop remains in charge.

These AI agents aren’t limited to tuning, either. They can manage ISA 18.2 alarms, audit logs, release-by-exception batch reporting, energy-use correlations and trace matrices from FRS (functional requirements specification) and FAT (factory acceptance test) documents.

Of course, in FDA-regulated territory, auditors will demand thorough records, version control and ironclad testing. And AI can help here, too, by creating documentation that organizes and fills in the reporting gaps so well that inspectors may never guess it took way less time.

Ultimately, we’re not torching the old temple. We’re giving the PID faithful a stable, validated PID loop fortified by AI.

Bill Mueller is the founder and senior engineer of Lucid Automation and Security, an integrator member of the Control System Integrators Association (CSIA). For more information about Lucid Automation and Security, visit its profile on the Industrial Automation Exchange.