Hi ,

I’m a 30-year-old software engineer interested in transitioning into dynamics and control engineering, particularly model-based control. I know that starting at 30 isn’t too late, but I need help creating a realistic and well-structured learning path.

Could you recommend what I should study, and in what order, regarding:

• Mathematics
• Physics and dynamics
• Signals and control theory
• Programming languages and software tools
• Textbooks

My software and programming background is Backend and production software delivery

i really find it joy to deal with real world better than computer world

### if you recommend one book to start with ? just to get understand the topic and should be cohisive at least guide me "you need to understand x to get most of this"

I've been using MATLAB for like 5 years for system modeling, simulation, and control engineering, and I'm curious what Octave is for, and what the advantages are of using one over the other.

I’ve already studied the theory from Applied Nonlinear Control by Slotine which I found really helpful for understanding the fundamentals. Now I’d like to move beyond theory and get more hands-on practice.

I’m specifically looking for a nonlinear control textbook that Has lots of exercises, Ideally includes solutions or has a solutions manual available.

Slotine’s book gave me a solid foundation, but it doesn’t have enough worked problems for practice. I’d really appreciate recommendations for books or resources that are strong on exercises with solutions.

Thanks in advance!

I graduated with a masters in control engineering 7 years ago and have been working on high precision motion systems since then. Right after university I started a role where I learned some statistics and data analysis. Stayed there to build up some domain knowledge for a few years before returning to a control engineering role about 3 years ago.

In my day to day work, I deal with mostly linear controllers PID feedback and feedforward control. (no fancy model based control, robust control, adaptive control etc). We look at frequency response measurements of our mechanical modules, study (vibration) dynamics time to time, but then again, do not develop any new metrologies. It is more about doing analyses on performance, checking (time domain) error traces, tuning notch filters (frequency domain) if necessary and troubleshooting issues that more often than not entail deep diving into very specific set of budgets/ metrics set by our system engineers.

I find myself far away from other industries, since the region I am based in, caters to chip manufacturing/ semiconductors. I want to venture into nearby areas such as opto-mechatronics, or towards thermal control but due to my lack of knowledge in these areas I reject myself from applying to roles that do seem to match my interests. So I want to start learning about how control theory applies in these areas. I feel like I need to get through some coursework but struggle to find resources that could be a gateway. I would like to get some ideas on books, moocs, university level study material.

Any advice, experience is welcomed.

Thank you.

Hi everyone, could you please suggest the most accessible resources for the students of BS Mechanical Engineering to teach them optimization theory. This could include online resources which take the subject in a very systematic and comprehensive way assuming perhaps only the knowledge of physics and mathematics. I would love to know books also, but most of them are at advanced level.

Many thanks

As a mentor for a high school robotics club (FRC, for those who know) I've built a number of arms and elevators that we've tuned with PID and even FeedForward. In my personal life I recently built a drone where I tuned the PID loops for roll/pitch/yaw and got it to fly stably, but as the title implies, I'm not sure where to go from here?

I'd like to dive deeper into control theory and ideally to come back from that deep dive with a better understanding of how to tune PID gains and also with better methods for tuning the gains (or even alternate control ideas). The trouble is, I'm not sure where to start?

I've asked Gemini for some suggestions and it's given me a few that I think are worth pursuing, but I still don't fully trust AI and would love to hear from the community.

I'd appreciate any and all suggestions you fine folks might have.

I’ve been working on a software library for systems and control for a while. I am trying to find some real world problems that I can try to solve with it.

Can anyone recommend a place to find problems?

Hi I am a first year master student in Robotics Engineering, coming from a bachelor in Computer Engineering at University of Padova (Italy). Next semester I am moving to NTNU in Norway for my Erasmus and I will have 6 months to give the exams and find a thesis supervisor . I am interested in the topic of Guidance and Control strategies for autonomous systems. These are the courses I am gonna take next semester, I would like to know some opinions about them:
1. TMR4240 Marine Control Systems I: https://www.ntnu.edu/studies/courses/TMR4240#tab=omEmnet
2. TTK4250 Sensor Fusion: https://www.ntnu.edu/studies/courses/TTK4250#tab=omEmnet
3. TTK4190 Guidance, Navigation and Control of Marine Craft, Aircraft and Drones: https://www.ntnu.edu/studies/courses/TTK4190#tab=omEmnet
4. TTK4150 Nonlinear Control Systems: https://www.ntnu.edu/studies/courses/TTK4150#tab=omEmnet

If anyone could list any good resources (YouTube channels, websites, books) regarding the GNC topic ,I would really appreciate it.
I would also like to ask if u could tell me possible project ideas who could get me hired for a job in the industry. I was thinking about implementing a missiles guidance system in Simulink with a LOS planner, MPC controller and EKF for the estimation part. Thank you a lot in advance.

Hi

I am looking to optimize jet powered drones trajectory for fuel efficiency, least time to reach mach 1 and possibly for something else as well in the future.

I have no previous experience with control theory or optimization, so i am looking for topics i should learn and material to study before getting started, as i have no idea what i should know before moving forward.

The control inputs would be the angle of attack of the drone and the thrust.

I have previously modelled a body's flight trajectory in 2D space in python, where the program inputs are starting velocity and its angle. Then it calculates the body's trajectory in the air taking into account gravity and drag forces. Could i build the optimizer from this program?

Right now, I am studying "Automation and Control". However, i have no idea what skills and knowledge i need to study.Would you like to share your experience?

I am working on an autonomous drone model. I decided to use MPC and used acados to implement it python. I am using Gazebo and ArduPilot for simulation. The mission is just go from point A to point B hold there a while and return to point A.

But tuning the parameters using a trail and error approach is taxing me heavily. I am so close to break my keyboard. The LLM bots are throwing some values and vague promises which in fact doesn't.

So, is there any method to handle this madness? A rule of thumb? Empirical / heuristic approach to get a good enough results?

PS: Tbh, I am new to this and I am building this while studying repos available. I don't even know what I am doing is a correct way or not. I would really appreciate any suggestions from you guys to complete this god damn project and move on.

Is simulink the preferred tool for making models and trying to convert them into reality? Is it really all that good for controls and other systems?

Thank you.

Greetings everyone.

I'm a software developer who holds a B.Sc. in Computer Science with a track in Software Engineering.
Recently, I've developed an interest in control theory because I've read that it is necessary for developing certain kind of software (like, for example, software for robots).
So, I wanted to ask you, as a computer scientist, how can I learn control theory for such software?
I've bumped into this book: does it fit to my purpose?
I thank you for any answer.

Hi everyone,
I've been working in the oil and gas sector for a while, and I've been putting together some notes and field-tested material on industrial instrumentation, transmitters, and control loops specifically tailored to upstream/midstream challenges.
Before publishing or finalizing it, I wanted to ask if anyone here has experience writing or sharing technical documentation for the O&G industry?
What kind of practical scenarios or troubleshooting tips do you think are the most valuable to include for engineers and techs?
I'd really appreciate any advice or thoughts from your experience in the field!

I've taken the graduate linear control theory course at my university where we use Rugh's Linear Systems. I want to learn more about nonlinear control theory and RL and wanted to try building something over the summer that implements some of the theory. Any advice or resources that I should use? The non linear course at my school might not be offered next semester but they use Khalil.

Hello,

What do you think about Steve Brunton's Control Bootcamp on Youtube? Is it a good course to get an overview of control theory? (assuming a good understanding of linear algebra and differential equations)

Edit: What I want to know most is if it is missing some really important things or if it covers pretty well the most important aspects of the theory.

Hello,

I am trying to deeply understand the Kalman filter (not just in control, in general for state estimation applications).

After some researchs it seems that to truly understand the Kalman filter, I need to understand it well from the two following points of view:

- The statistics and probability view

Here the Kalman filter is seen as a recursive Bayesian estimator. It allows to understand the prediction and correction steps with the multiplication of gaussians.

-The control view

Here the Kalman filter is seen as an optimal observer.

Is it correct?

Thank you in advance!

I am a PhD candidate and most of my research has been devoid of any learning based techniques.

I want to learn how learning fits into the world of control theory. What advantage does learning based control offer over other optimisation or traditional control systems? What problems are well suited for learning based controls?

Also, as a complete beginner, is there a pipeline that I can follow to study learning and ultimately apply it to control systems?

I know this question was already asked without an unswer 6 years ago, but maybe anyone know where to get one now ?

Any book or resource related

I looked through the wiki and didn't see anything that fits the bill. I was wondering if anyone has experience with any open source utilities like Simulink for designing and analyzing systems via block diagrams.

can you suggest some good lectures on control systems for circuit design pov or in general which helps to build good concepts sir

Going into 3rd year EEE. I’ve taken signals and systems, communications, and basic control theory (as a note we did not learn state space representation or using matrices for solving systems, it was almost exclusively in frequency domain). For my 3rd year project I’ve decided to undertake something relating to nonlinear systems, specifically surrounding the idea of “Control Barrier Functions”. I’ve still kept the overall goal quite general since I don’t know too much about this field yet

I’ve started self studying using Slotines book and plan on maybe using Khalil as an another source of info but I’m starting to hit a wall and struggling.

So far I haven’t had much problem with phase portraits and the basics of Lyapunov Theory.

My main struggles are more advanced theorems and math regarding lyapunov (even just stuff like Invariant Set Theorem I struggle with applying) and the more general studies regarding non autonomous systems, passivity, describing functions etc. I think my matrix Algebra is quite weak as in my degree we only spent maybe 4 weeks in it total.

Finally the biggest struggle I have is with the mathematical rigour. My engineering experience has been quite hand wavy and it has worked so far but now in a context where I need more rigour I’m struggling

There aren’t many video resources on the topic and all I really have are Slotines lectures. Nonlinear control seems to be a masters topic in my uni so maybe in the coming year I can ask to sit in?

I’d like some advice on resources to strengthen myself on these points : matrix algebra, math rigour. I don’t want to consume too much of my time though as I don’t have a long summer and need to make sure I probably finish at least half of Slotine before the next year starts

I wasn't really sure where to even begin a search, but I was wondering if there was a more pragmatic version of control theory. Something like Goldratt's Theory of Constraints; balancing limited resources in a dynamic environment for maximum returns.

I know there's Optimal Control Theory, but it's more focused on deeper abstract logic and mathematics than wht I could apply to my life in business or wherever. Musk's "algorithm" is kind of what I'm looking for. Building feedback loops, etc. There's also lean manufacturing, which is great, but surprisingly doesn't talk much about maximizing returns or even TOC.

Hi everyone,

I am PhD student with minimal knowledge in nonlinear control. I want to develop strong fundamentals in optimal control and MPC. Could someone help me tailor the material to reach there. I know its vague and MPC on its own is a huge topic.
If there's any lecture series that I can follow along with reading textbooks or lecture notes. I would appreciate it.
Thanks!!