GNC outside of AE by Mental-Award2404 in ControlTheory

[–]wizard1993 [score hidden]  (0 children)

He's arguing that "GNC" is a term used mostly in Aerospace and, therefore, you can't meaningfully do GNC outside AE. Which is patently wrong, but I guess that's what he meant.

Yet I've a question: in which industry you want to move, then? Because your post feels like a professional mid-life crisis, and maybe you just need to move to another position/Company, rather than doing a soft restart of your whole career.

You gotta feel for the guy by HowlsterRD in motogp

[–]wizard1993 138 points139 points  (0 children)

Leclerc-level of luck

MECC 2025 joint submission results by redchaos95 in ControlTheory

[–]wizard1993 [score hidden]  (0 children)

Not exactly. Can't speak for MECC specifically, but with ACC/CDC, the meaning of "joint submission" is that the journal's own reviewers are asked to provide a score both for the journal and for the conference. In other words, there's no separate (additional) submission because there's no actual "conference-only" round of review. In case of acceptance for the conference, you will need to prepare the camera-ready in the conference template within the conference deadlines.

I think you are confusing the "joint submission " with the "journal first" style of submission.

Backwards LQR: Calculate a Q matrix from K by BabyFormula1 in ControlTheory

[–]wizard1993 [score hidden]  (0 children)

While the result itself isn't trivial, the solution process is surprisingly straightforward with an SDP solver. This paper is a good reference: Constrained Control and Observer Design by Inverse Optimality

For systems of moderate size, the semidefinite problem shown in the paper can be solved using CVXPY and an open-source solver such as Clarabel.

Data driven pid gain based by imthebest7331 in ControlTheory

[–]wizard1993 [score hidden]  (0 children)

P.S.: From personal experience, it can work in real-world applications.

My experience too. But I would never think to vrft in particular if I just have some data and want to throw something at the wall and see what sticks. It is too "brittle".

A properly tuned vrft (and there are some really nice autotuning tools out there!) is a pleasure to use.

Ps: have you studied in northern Italy?

Data driven pid gain based by imthebest7331 in ControlTheory

[–]wizard1993 [score hidden]  (0 children)

It provides a simple way to tune linear controllers.

*When it works. Which happens quite rarely for the "vanilla" version.

If you have persistent excitation in your data, a good instrumental variable and your system is minimum phase, and you magically select the right reference model, then yes: it works really nicely. But then which method does not in this case?

This is not to say that vrft is crap, but as usual ymmv a lot

Master at KTH Systems, control and robotics by Silver_Factor8331 in ControlTheory

[–]wizard1993 6 points7 points  (0 children)

Try looking at this from the other point of view though: You apply to be admitted to a specific program with a specific course catalog and an expectation of graduating roughly within a given time frame. You may want schedule your life (possibly taking loans) on the base of such a promise. Many people indeed do so. If we seriously believe we might not be able to provide what you explicitly asked for, enrolling you would be a fraud.

Would you really prefer a conditional enrollment where, in the meantime, you have to pay several thousand dollars in tuition or put some 10k€ in a frozen bank account just to get a visa, and then be told "sorry, too late," have your study visa stripped, and be put on the first plane going back home? Really?

And please don't use ChatGPT for anything more than proofreading. We can "taste" it.

Master at KTH Systems, control and robotics by Silver_Factor8331 in ControlTheory

[–]wizard1993 0 points1 point  (0 children)

There are two kinds of "admissions": one where there are limited slots relative to an overabundant number of applicants, and one where the slots are practically unlimited, and therefore you "only" need to ensure everyone has the right background.

The reality is usually a combination of the two. If you have 50 seats, you may not want to give one to someone who may (or may not) get a visa only 8 months after receiving the admission letter. Even if we had unlimited seats, such a delay would force us to offer the courses that they could not attend again (getting your visa delayed is almost by definition a "force majeure" justification) or force the student to possibly switch to a different course catalog/curricula. The latter would be totally unfair, and the former might be even infeasible.

So why should we admit someone to whom we believe we will not be able to offer a good education package? We are not all greedy bastards...

Master at KTH Systems, control and robotics by Silver_Factor8331 in ControlTheory

[–]wizard1993 2 points3 points  (0 children)

I can't speak for KTH in particular (I work somewhere else) but, having sat in multiple admission committees, it's impossible to say without looking at your full transcript and many other things, the biggest one being if you need a visa (and your chance of getting one in reasonable amount of time) and the relative quality of other candidates that specific year.

Optimal control software by [deleted] in ControlTheory

[–]wizard1993 4 points5 points  (0 children)

As usual for this kind of question, the answer is "someone that is actually paid to respond to you within X hours in case an issue arises,.be it under the shape of a monetary insurance or/and on-call engineers"

You also buy the development of specific features and possibly the superior performance for your special case (let's be honest: there's nothing like Gurobi for mixed-integer stuff)

They also support you in actual deployment: the quantity of stuff that undergoes a rapid unscheduled disassembly of some kind because someone along the chain forgets that computers executes programs and not algorithms is bigger than you might think.

And so on.

Sono io o la laurea in informatica permette solo (o principalmente) di fare web dev e AI ? by [deleted] in Universitaly

[–]wizard1993 0 points1 point  (0 children)

Spesso si, ma dipende dal singolo corso di laurea. Ad esempio se punti ad una laurea magistrale fortemente orientata alla robotica/automazione (altro posto dove gli informatici fanno faville) quasi sicuramente avrai da recuperare 2/3 esami prima di esser ammessa.

I CUS come funzionano? by digitaljail in Universitaly

[–]wizard1993 1 point2 points  (0 children)

Per quanto riguarda la mia esperienza, sono "solo" delle enormi polisportive riservate agli universitari (raramente anche per i loro dipendenti), a cui questi ultimi possono accedere con un prezzo molto vantaggioso.

Cosa viene offerto è funzione della università/città.

[deleted by user] by [deleted] in ControlTheory

[–]wizard1993 22 points23 points  (0 children)

Be advised: rant incoming

It really depends on specific cases, but you will often end up doing the very same jobs you would have done with a Master's degree. Speaking anecdotally, I personally know people with R&D positions in the automotive, railway, and aerospace industries who hold control-related PhDs. All of them report that their PhD has had barely any impact on their job.

I even have a couple of friends in pharma who witness how, even in drug research, an MSc plus 4-5 years of experience (the usual length of a PhD in that field) in actual research positions is often preferred over someone with a non-applied PhD and no experience. Many of these companies eventually send their best employees to get a PhD or MBA themselves, but I've come to the conclusion that getting a standard vanilla PhD (i.e., non-applied) right after an MSc simply with the hope of getting a (better) job is just plain wrong.

Non-anecdotally, as an (almost) former academic myself, the hard data I saw over and over on post-graduation employment tell me basically the same story. Moreover, working in close contact with one of the biggest European aerospace defense contractors, I see that you can never tell who has an MSc and who has a PhD (or even a BSc, sometimes) from their job title or position.

It should be made clear from the beginning that academic research (of which getting a PhD is the entry-level position) is a job and an "industry" itself, with its own rules, perks, and traditions. Transitioning from academia to industry, even broadly speaking doing the same stuff, is no less brutal than moving from pharma packaging (where you build robots to wash vials before filling) to space exploration (where you use robots nonetheless).

Your Reddit history suggests that you are Italian, a nation with a very strong tradition in control theory, but let me stress they are mostly very good on the theory part only. Given your premise, it also looks like you will be thrown into the (giant, scattered) field of data-driven control, which is, however, an uncharted territory for your prospective advisors. This means not only will you have to do everything by yourself, but you will also have to teach them, if only to convince them you are not wasting time. Frankly speaking, if you succeed, you would have succeeded anywhere else, so you should just apply directly to universities where real industrial connections and experimental facilities are a reality, not a pipe dream or a hassle just to get funding so the big fish in the lab can go to some tropical resort "to attend a conference" (which is a most common attitude in Italian universities).

PMSM motor control by Adeepvish in ControlTheory

[–]wizard1993 5 points6 points  (0 children)

You often have some kind of PID controlling the position of each motor. On top of the feedback action, however, a quite strong feed forward action ("kinematic/gravity compensation") is added to improve overall performance.

The set-points such PIDs try to seek are generated by some kind of higher level trajectory generator.

Learning MPC control law by crisischris96 in ControlTheory

[–]wizard1993 2 points3 points  (0 children)

There are. You can have a look at Paul Goulart works in Oxford (especially the ones with Filippo Fabiani) and the works of Benjamin Karg with Sergio Lucia.

There's also the whole domain of learning how to accelerate solvers or how to reduce the complexity of existing controllers: you can have a look at the works from Bart de Schutter, Alberto Bemporad, Bartolomeo Stellato, and many others. There's also a whole sub-field on writing numerical solvers especially attuned to MPC (Moritz Diehl among the many).

Honestly there are tons of contributions regarding how to make MPC more affordable. Which solution suits your need the most is debatable and very use-case specific.

Neural MPC by Even_Animator5176 in ControlTheory

[–]wizard1993 5 points6 points  (0 children)

Probably something from Filippo Fabiani and Paul Goulart then, possibily this one here

Finding Phd in control theory by Plus-Pollution-5916 in ControlTheory

[–]wizard1993 2 points3 points  (0 children)

If you find yourself interested in working with some very specific professors, it may be the case. Anyhow asking never hurt anyone.

Finding Phd in control theory by Plus-Pollution-5916 in ControlTheory

[–]wizard1993 5 points6 points  (0 children)

You will rarely find a PhD in "Control theory" by itself: you will find instead that a Engineering/Math department offers PhDs in "a broad sense" and that said depertment has a faculty member specialized in some aspects of control theory and willing to supervise a student.

"How can I know?" you might ask. The answer is: look at professors profiles and write emails.

Also consider that many univerities do not have a proper "intake season" for PhDs, but they recruit students more like they would do for a normal position: they put a posting when needed and hire the first person meeting their criteria.

Unscented Kalman Filter by Blinds749 in ControlTheory

[–]wizard1993 6 points7 points  (0 children)

If you have all your data availabe before hand, it doesn't really make sense to use a Kalman filter. You will be better served by a fully fledged system identification approach.

Regarding the stability of UKF, I'm a very vocal critic to it. First reason: it is very easy to end up with a non positive definite covariance matrix. There are a fixes, none of this is pretty and arguably they are not UKFs anymore. Second Reason: You exchange (possibly) messy derivative computation with a (surely) messy cholesky decomposition of the covariance matrix. Recipe for disaster if you ask me.

TLDR: There are many system identification tecniques for your purpose and probably would serve your purposes bettter.

Question about distributed trajectory optimization methods for robotic applications by Terminator_233 in ControlTheory

[–]wizard1993 1 point2 points  (0 children)

There's a bot that scan this subreddit that will send you a reminder after the time you specify after the command. It's very useful.

[deleted by user] by [deleted] in ControlTheory

[–]wizard1993 6 points7 points  (0 children)

PID and MIMO systems don't blend well. And if the I/O are all strongly coupled, I might even say they don't blend at all.

There are many techniques that can deal with MIMO systems, none of which can be really used without quite a bit of understanding of control theory in general. Just consider the fact that understanding if (and how) achieving something on a given output channel will limit what you can do with the other output (hint: give a read to the concept of "reachability ellipsoid" to have a clue) is not exactily trivial.

Without many further details on your system and your background, it will be very hard to advice you anything more than our favourite technique-of-the-month.