May 28, 2026 · 1 hr 1 min · 12 segments
Dr. Victoria Serrano spoke with us about STEM outreach, fostering curiosity, and inspiring students with engineering education. Victoria is a professor at the Technological University of Panama (her…
Victoria SerranoGuestElecia WhiteHostChristopher WhiteHost[laughs] Uh, you did your PhD, uh, at Arizona State University, and your thesis was in PID controller tuning and adaptation subject to quantization effects.
And I have to admit, this sounds super interesting to me, but I think I might be one of the few.
bit?Yeah, and this was, um, a project that, uh, that w- we were working with another professor, eh, in another area which was not control system, but he was most more specializing in the, eh, power electronics area.
And the idea was just to study, eh, what, eh, what were the defects when we were having, uh, different scenarios when, eh, the different devices of the buck converter were just getting degradation.
Because over time, I know it's, it, it should take some time, eh, some considerable amount of time to degrade, but when you, we talk about devices such as inductors, capacitors, or, eh, whatever device, eh, they don't measure the same level as when they were new.
So what we were trying to do with this project was just to, eh, describe the different scenarios when they were, eh, changing their values, for example, 5%, ter- 10%, 20%, like five or six different scenarios.
And then we were trying to, eh, what we did was, was to, to, eh, design the controller for that specific, uh, scenario.
And then we were just choosing the right controller depending on the scenario based on, um, it goes like a rule in which we were choosing the right one based on that rule.
You have, you had to minimize, uh, a specific parameter just to choose, okay, this is the, the perfect fit for that scenario.
And that's why this was adapting because, uh, when we, eh, had the different scenarios, we, we already designed the, the different controllers, but then we had to choose the, the best one based on that parameter that we wanted to minimize.
I don't know if I'm, I explained what I, what I, I did with that specific, eh, specific research.
You were tuning a buck converter that was degrading over time because it was aging, and you had a-
... controller that would, uh, make the output be the same, but it was a, a set of several controllers-
... that you chose based on the heuristics, uh, uh, the characteristics currently in the system.
It, it was like a, a metric that you had to, to fulfill so that you could choose the specific controller.
So, eh, and, but that, eh, if, if we've, eh, we were not getting close to that, eh, minimum value of that metric, then we had to choose the next controller.
[laughs] Uh, you did your PhD, uh, at Arizona State University, and your thesis was in PID controller tuning and adaptation subject to quantization effects.
And I have to admit, this sounds super interesting to me, but I think I might be one of the few.
bit?Yeah, and this was, um, a project that, uh, that w- we were working with another professor, eh, in another area which was not control system, but he was most more specializing in the, eh, power electronics area.
And the idea was just to study, eh, what, eh, what were the defects when we were having, uh, different scenarios when, eh, the different devices of the buck converter were just getting degradation.
Because over time, I know it's, it, it should take some time, eh, some considerable amount of time to degrade, but when you, we talk about devices such as inductors, capacitors, or, eh, whatever device, eh, they don't measure the same level as when they were new.
So what we were trying to do with this project was just to, eh, describe the different scenarios when they were, eh, changing their values, for example, 5%, ter- 10%, 20%, like five or six different scenarios.
And then we were trying to, eh, what we did was, was to, to, eh, design the controller for that specific, uh, scenario.
And then we were just choosing the right controller depending on the scenario based on, um, it goes like a rule in which we were choosing the right one based on that rule.
You have, you had to minimize, uh, a specific parameter just to choose, okay, this is the, the perfect fit for that scenario.
And that's why this was adapting because, uh, when we, eh, had the different scenarios, we, we already designed the, the different controllers, but then we had to choose the, the best one based on that parameter that we wanted to minimize.
I don't know if I'm, I explained what I, what I, I did with that specific, eh, specific research.
You were tuning a buck converter that was degrading over time because it was aging, and you had a-
... controller that would, uh, make the output be the same, but it was a, a set of several controllers-
... that you chose based on the heuristics, uh, uh, the characteristics currently in the system.
It, it was like a, a metric that you had to, to fulfill so that you could choose the specific controller.
So, eh, and, but that, eh, if, if we've, eh, we were not getting close to that, eh, minimum value of that metric, then we had to choose the next controller.
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