Getting in tune with Ziegler-Nichols

I recently visited a production facility of one of my former students and heard he was doing a fair amount of controls work. The professor in me was proud that some of what I taught in the classroom was being implemented.

I asked the engineer to show me some of the applications. He took me over to an extruder that had a proportional (P) controller closing the loop. He indicated that he had replaced the original standard “bang-bang” thermostat with this new controller, and the results were wonderful. While I was glad that my student used some of his training and congratulated him, inside I was a bit distraught that he had only implemented a P controller. I thought, “What happened to all of those great design tools like frequency response, root locus, and robustness that I taught my students in my lectures?”

So I asked if there were more advanced controllers in use. His boss, who was with us, smiled and told me that they had some problematic systems that required some advanced controls concepts. She showed me some precision motion systems that had PID (proportional-integral-derivative) controllers on them. I asked how these were tuned, and was informed that they mostly just “turned the knobs” until they had the right performance.

Of course they remembered that each of the three PID gains has an effect and generally knew which way to turn the knobs. I asked them if they tried Ziegler-Nichols tuning. They said that turning the knobs seemed to work, and Ziegler-Nichols was something very far back in their memory, and they did not even consider it. At that point I could not help myself and asked if we could tune the systems with the Ziegler-Nichols approach. They laughed and told me that we could try to tune the system, and I could invite anyone I wanted, even Ziegler and Nichols. Sure enough, after a few step responses, we had the system working perfectly. They told me that using this technique was definitely better than turning knobs for a few hours.

Many engineers implementing controls algorithms on typical plant hardware are hindered by the limits of PID control. With tuning done by hand, more advanced controllers (lead, lag, optimal, adaptive) are difficult if not impossible to implement. With the advent of the next generation 32-bit controllers and supporting software, I believe that we will see a change over the next few years.

Many modern digital “PID” controllers look similar to and mimic the old analog PID controllers. Thus, they can be programmed with any control algorithm and tune themselves. The software supporting this revolution is the next generation of graphical programming tools, such as National Instruments’ LabView and Mathworks’ Simulink. These software packages are very familiar to our students and to many controls engineers in industry.

For example, LabView’s real-time capabilities are now ported to a number of 32-bit processors and enable embedded control applications. Advanced auto-tuning for PID controllers and far more advanced controllers and tuning algorithms can be implemented. Using the intuitive, familiar, LabView language, engineers can quickly program 32-bit processors with advanced control algorithms that can monitor, detect changes, and update the control to optimize system performance. With new hardware and software, I’m training new and returning control engineers with clear, easy, inexpensive tools, enabling them to take advantage of all that their professors taught them in many exciting lectures.

The day of hand-tuning PID controllers is ending. Improved performance, ease of use, low cost, and training will put Ziegler and Nichols in the driver’s seat, and, packaged in graphical software, will be less intimidating than when you first met them in your undergraduate controls class.

Author Information

Thomas R. Kurfess, Ph.D., P.E., is BMW Chair of Manufacturing, Clemson University International Center for Automotive Research.

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