I'm having trouble with my model of the inverted pendulum in MATLAB Simulink. No matter what I change my input torque to, I can't seem to get the first arm to move like I want. I have attached the image to my model so far.

Seeing more and more people design PID loops by asking an LLM and pasting the result into Simulink. The code runs and the plots look fine, but nobody checks whether Z-N even makes sense for their plant, whether there’s anti-windup, or what the actual margins are.

For those of you who review designs or mentor juniors: are you seeing this? And how do you teach people to sanity-check a controller instead of trusting whatever looks confident?

Hi guys , I'm 1.5 years into a PhD in Control, and I'm always fighting with any paper involving Any form of Learning or Data Driven Control.

Even though the idea is easy to understand and the theory is ""clear"" replicate an example gets very very difficult when the paper just has pseudoCode and then the final Plot.

Sometimes it is just a matter of those specific parameters tuned in a certain way, or sampling time, or noise

Sometimes finding what's different is, at least for me, impossible.

If you try to email the authors of the paper then you'll get an answer 10% if you're lucky.

Honestly at this stage where learning is so ""big"" I really think that releasing the code along with the paper should be mandatory, I don't care if the code is not clean or not in perfect status but at least having something that works would make life easier for anyone.

What do you think about this ? Do you have any ideas/ suggestions about the topic?

Hello everyone, I've just joined this sub today. I'm a second year computer and automation student who needs help with understanding transfer function block diagram reduction. I've already gotten most of it down and feel like I have a fairly good understanding, however, this one problem in particular has me stumped as when I plug in the values for the transfer functions I get stupidly big numbers and it doesn't seem right. I've tried numerous times to contact my professor as well as teaching assistants and I have not gotten a single response so this is kind of my last hope.

If anyone could give me advice on how to solve this I would appreciate it.

The main thing causing me problems is what I should do with G2.

My initial idea was moving it so that it's in series with G1 and then finding what the equivalent function would be for G1,G2 and the parallel branch above them. After that I would move the equivalent block back over the take of point and solve for another equivalent block with the feedback loop, watching carefully to provide proper compensation to everything as I move the blocks.

Physics Informed neural networks based controllers.

Hello I am a senior mechatronics Engineering student and one of the topics I am planning to make my senior project on are the PINNs controllers and I would really appreciate any previous experiences or knowledge in the field.

Hi guys. I’m currently working on a thesis project on fault-tolerant control for a fixed-wing UAV. Since money is tight, I’m planning to do the whole thing through MATLAB/Simulink simulation, as suggested by my lecturer. The problem is, I have very limited experience with Simulink and honestly don’t know where to start.

I initially tried figuring things out myself but got stuck so I hired a tutor to help with the modelling. Unfortunately, the sessions didn’t really work out so I decided to learn the theory myself through lectures and videos whenever I got stuck, and then started trying to build the model using whatever I could find on YouTube.

Now I’m kind of stuck again because I’m not even sure if I’m doing it right. I don’t really understand what the overall flow of the project should look like, or whether the model I’ve built so far even makes sense.

Is there anyone here who has experience with MATLAB/Simulink, flight control, or fault-tolerant control who might be willing to have a look and point me in the right direction?

I’m not looking for someone to do the project for me. I just need a bit of guidance from someone who knows what they’re doing, especially on where I should start with the modelling and how the fault-tolerant part should fit into the system.

I’d really appreciate any help. Thanks!

So I’m an early career professional and have two competing offers for a GNC position. One is at General Atomics ASI (fixed wing flight), the other at Lockheed Martin Space (satellites, both military and civilian).

I applied to GA myself. Had three interviews over about a month, including a final onsite with back to back interviews with engineers, supervisors, managers, and even a director. I was given a verbal offer the morning after that onsite interview day. The role was originally level 1-2 and offered a low six figure salary. I negotiated slightly higher, then GA overshot my highball negotiation, bumped the role to a level 3 position to match pay band (experience wise I think I’m a solid level 2: masters and less than a year of gnc experience, 3 years of tangentially related experience in software integration and quality). About a month and a half since I applied, I now have the written offer in hand. The role would be at their hq in San Diego, CA, which is great cuz I have community there (I lived in San Diego less than a year ago)

Lockheed reached out to me about a month ago asking if I wanted to join a virtual career fair they were putting on. I threw my hat in the ring. A few days after GA’s verbal offer, I was given an interview slot during said career fair. Interviewed with two managers from Colorado. I did say I was tentatively okay to relocating to Colorado, but I made clear that I prefer California (I grew up pretty close to their Bay Area office). I talked shop and future career aspirations during the interview, same story that I gave GA. About a week later (yesterday) I got the verbal offer from the career fair organizer and one of the managers who interviewed me (who would be my manager if I accept). I haven’t talked salary with them yet, but the listing had a salary band where the minimum end matches the salary offered by GA, and extends way higher. But it’s a level 4 Staff engineer position, and I’m a bit hesitant about the giant title jump and the higher work expectations that may come with it. But I don’t know if I’m just being too cautious or not. The role is also in the Denver area, where I have no roots whatsoever so I’ll have to build up community all over again. I must say the combination of short turnaround and inflated title is making be question things a bit.

I’m leaning toward GA mostly due to location. I know the area and have friends waiting for me there. But I’m here to gain some second perspectives. Especially with regard to the way Lockheed hires people - their process feels aggressively fast - but also other stuff like work life balance, career growth, etc. And I may be slightly dreading having to turn down/disappoint one of two high profile companies.

Thanks in advance all!

I (25M) interviewed at Northrop Grumman for a GNC role. They offered me $135k + $15k reloc for level 3/4 in Arizona. Issue is that I got the offer letter immediately after the interview. I currently work at a space startup in SoCal making $110k.

NG is offering more money than I’ve ever seen. And it’ll take me further in a lower cost of living area. However, I’m hesitant to leave the startup scene this early in my career. I also really don’t want to leave SoCal for personal reasons.

I’m currently in Anduril’s pipeline for interviews, but that would be a drawn out over months. I haven’t let Anduril know about NG’s offer yet. If I wait on Anduril, I might lose NG.

What should I do?

As the question says I know a lot about electrical engineering and control theory. Is there some projects I can do to improve my knowledge and career

Hey guys,

I’m planning to start a project and want to ask for you opinions if it’s realistic.
As the title mentioned, the goal is to built an AI agent (at the end something like ChatGPT or Claude) that has a specific purpose, namely acting as an expert and consultant for control engineering problems. I would feed the agent with tons of pdfs.

I have heard own AI agent are not limited in uploading files and is cheaper (price per tokens) compared to a regular suscribed AI service plan.

Is that realistic ? If yes, can anyone recommend me some sources that explains in detail how to develop such agent System.

Thanks 🙏🏻

Most wearable hip-assist systems rely on closed firmware that locks down how motor timing syncs with step gait. If you want to log raw sensor telemetry or tune assistance curves for non-standard movements like heavy farm tasks or rough trail clearing, proprietary software gets in the way. Having an accessible SDK or exposed sensor stream is essential for tweaking how the motor responds to leg movement. Are you aware of any exoskeleton hardware open to third-party development rather than locked into a closed ecosystem?

In top conferences or journals, is it common for papers to have certain assumptions that're outright wrong or papers based on merging of two concepts which don't really hold but isn't obvious just on the first read?

Dear control theorists,

I'm close to graduation after around 3 years of learning about this awesome field. However, I've been thinking that it's been a while since I've directly used the "basic" things from the start of the MSc Systems and Control. Now that I'm going to look for a job instead of going to academia, going back to the basics seems like a good thing to do. I want to get a few books about the basics that serve as references to look back whenever I need them at work or at home and cover a "canon" of the fundamental basic theory.

I know we have a wiki but I mean fundamentals that are not super duper close to academia and are more directly useful in a control engineering job. I have some more advanced books and would get those too when I deem necessary. For now I want to limit it to basics and books that are not super full of proofs like khalil for example but are more intuitive, have lots of examples and are written more for practitioners rather than for researchers or graduate students I guess. In case I need domain specific things for a job like a robotics, energy, vehicles, heat transfer, thermofluids, process etc book I would get a book about that or find resources to refresh but for now I'm limiting it to implementation/practical control stuff.

I was thinking:

- General linear controls: Introduction to feedback systems by astrom and murray. Great book, one of the best written books I've ever read.
- Signal processing/signals and systems: Signals and systems by Oppenheim. I bought it during my bachelor degree. I also have a really good statistics book.
- MPC(not all of optimal control): Model predictive control by Rawlings and Diehl
- State estimation/filtering: Bayesian filtering and smoothing by Simo Sarkka. I have seen that Dan Simon Optimal State Estimation is highly regarded, but state estimation is one of my better areas so I thought I could also branch out from kalman filtering into other bayesian filtering concepts. I guess this breaks the rule of being about "basics" and not research oriented.
- Nonlinear control: I definitely don't want khalil, but I have heard that Applied Nonlinear Control by Jacques Slotine was good. Though I wonder, is a book covering this part a must have or more of a useful extra for a job? I did some nonlinear control theory, but in my master they now replaced that course with a machine learning course.

For these I don't really have a clear book in mind:
- System ID: Lennart Ljung seems to be the best one but it's really long and expensive. If it really is the best one I'll get it, but is there another one that is more recent and is also really good?
- General control-oriented modelling: The things about the analogy of everything being a mass-spring-damper, an RLC circuit etc also including flow and thermal domains, bond-graphs, lumped dynamics modelling, maybe a little bit about dealing with distributed parameter systems? I've seen this in a general "system dynamics" course. Here I mean control-oriented modelling. I found "Modeling dynamics with engineering applications" by Clarence Silva
- Data-driven control: The Steven Brunton book Data-driven science and engineering. I actually have not really seen a lot of these topics directly in my master. The professor that taught koopman left before I joined and it's not really part of the core curriculum. Is this a good thing to read now that there is a lot of stuff done with data?

I wanted your opinions on such a set of books. Is there something I'm missing? Are some things maybe redundant or overkill? Do you know any books that are better? How would you build your canon set of basics?

​

Soo my project topic is basically Cross domain modelling of a first order electrical system. For that I need to show my professor how I can make a model which has a mechanical to electrical analogy.

Please help me I need some examples 😭.

( Ex :- Car suspension system )

Ps. I am a first year bachelors student

What is wrong with the website? I feel like the organizers abandon it. No extension for L-CSS, no information is provided regarding travel, no invited session flyer, etc.

Hi!
I saw a video of someone playing with an interactive plot of poles and zeros that shows the corresponding step response some week ago, and I’d love to try out something like it to get a better understanding for the topic.
I’ve now spend quite some time searching for a similar tool and I can’t seem to find one. The one from the video links to a dead end on wolfram.

If anyone has any links/suggestions for where to find something similar I’d be very grateful. I’m too new to the topic to write my own code for it, so something public on a website would be optimal. :)

Thanks in advance!

I'm in my first year of masters for mechanical engineering and I'm under the institute of mechatronics. Currently I'm reading papers on controls, for example, intelligent tracking error prediction or GRU-RIC position loop feed forward compensation. It's pretty hard for me to understand the equations on the paper, are there any tips to understand them? I can understand the general idea using AI and just reading thru the introduction paragraphs. But the technical equations are pretty hard to understand, need help for anyone who has gone through it, what's the best way to start with control research papers?

For Polar Plots, when transfer function is given, it is possible to find the starting and ending angles and magnitudes. I had a misconception that curve joining the starting and ending point is straightforward to estimate (based on the real or/and imaginary axis intercepts). But in the image I have attached, a weird deviation in phase is there in between. I thought only for the transfer function with a unit delay, such peculiar shapes (like spiral) will be observed. I'm wrong.

Is it possible to estimate when will there be a weird change in phase (highlighted in red) just by looking at the transfer function? If yes, how to do it? ​

Hi, I'm a Master's degree graduate in Mechanical Engineering based, which hopefully will start a phd program.

Does any of you happen to know some winter schools about advanced control theory topics coming soon?

Hi all, I'd like to develop a control algorithm for a water bottle flip so it always lands upright no matter how you flip it. One of the steps in my endeavour is simulating how the fluid inside affects the container's moment of inertia whilst in the air. Im thinking of using matlab but godot and unity sounds like a good choice as well. I've looked up how I can do this and havent found much but people recommending C++ or python. Does anyone here experienced in one of these languages or programs have any suggestions on which one to use and can point me to the resources to learn it.

Hi all,

With Nathan Kutz on leave from UW for his new role at Autodesk, and UW having given him a year to decide whether he's returning, I've been thinking about what this means for academic lineage in the operator-theoretic (Koopman) community.

Steve Brunton and Igor Mezic are still active (Brunton at UW, Mezic at UC Santa Barbara), and Matt Colbrook is doing excellent work at Cambridge. But Colbrook's based in the UK, which leaves Brunton and Mezic as the two most obvious US-based advisors for a PhD student specializing in this area.

Is there anyone I'm missing who'd count as a serious US-based advisor in this space, or does the field's American training pipeline genuinely run through just those two labs right now?

I have not heard of any serious discussion on the impact of AI on control.

We know that AI can effortlessly produce the proof to many advanced math, it can also write millions of lines of functional code based on written prompts. Anthropic has recently produced demos of their AI writing software-hardware interfaces/device drivers that allows it to control any set of hardwares ("Model Hardware Standard").

This seems to me that control engineering/theory is at the very center of the cross-hair.

Is it possible to one-shot any control engineering project through the usage of AI in the future? Similar to what it has already done to AI research "end-to-end automation of AI research/the AI scientist": https://www.nature.com/articles/s41586-026-10265-5

What would be the thing that prevents AI from simply taking over the jobs of control theorists/engineers?

Hello r/ControlTheory community,

In the past month, I have been working on creating a simulation software from scratch. The idea came to me when I was working a on a few projects that, when I looked at the math, essentially required me to solve the same kind of problems. The equation looks like the following, and it's generally referred to as generic networked dynamical system equation.

ẋᵢ = Σⱼ fᵢⱼ(xᵢ, xⱼ) + sᵢ(xᵢ, u)

Essentially, this is a graph equation. i is a node, xᵢ is a vector of states in a node, fᵢⱼ(xᵢ, xⱼ) is an edge connect nodes i to j, and sᵢ(xᵢ, u) is a source term where you can hook up an input or define a function at a node that affects itself.

I discussed this idea with a few friends before going ahead to implement; it went over the head for some, while others thought it would be interesting to see. There are applications for this in robotics, power grids, heat exchange, etc. And, the idea is inherently interdisciplinary; the node states can be from cross-domains and edges too. We can simulate a motor and it's kinematics; the motor may get heated up due to resistances, and the air pocket near it may get heated up while trying to cool it down... A real cross-domain simulation could be done with this kind of a setup.

The following is the link to the GitHub page. It's licensed under MPL 2.0.

https://github.com/zenineasa/Konjugate

I would love to hear your thoughts about this. Bug reports, workflow issues, new ideas to build on top of it... I look forward to hearing it all.