r/ControlTheory

Hello, I will be starting a MSc in Systems and Control at TU Delft. How is currently the job market in systems and control? Specifically for R&D positions. I'm also considering a PhD, do you think it will bring some advantages in job searching?

Instead of just tuning PIDs

Assuming I have a PhD to do with controls

Note: we use fixed wing uav/drone

I am primarily preparing for a drone competition. In the competition, we need to perform docking maneuvers with other drones using a camera. For a successful docking, we must keep the target drone's size in the camera view greater than five percent and at a maximum distance of 50% from the center on both the horizontal and vertical axes for 4 seconds.

Currently, we control roll pitch and throttle with 3 separate PIDs. I want to switch to an MPC controller, but instead of manually finding the coefficients in the matrices through trial and error, is there a way to somehow transfer my PID coefficients to the MPC and just do fine-tuning?

My English isn't very good, I hope I've explained it well enough. I'll try to explain it more clearly in another post using translation tools like Gemini, etc.

Hi! I am not an expert yet but a rather new graduate working in controls, but I want to share hereby my thoughts about some topics I wish I had paid more attention and time back then at uni. Especially topics that are relevant in industry. Also I think people with many years of experience in field can add and share their ideas.

1. Linear Algebra: Try to learn it well. Take matrices and learnhow you can transform them in another form, like reorder, inverse, transpose, normalize etc. Check Similarity Transformations.

Try to understand eigenvectors and eigenvalues. What do they represent in a physical system? Check State Space forms, understand what the states mean.

2)Mechanical Vibrations: For those who are gonna work on mechanical systems this is quite relevant. Everything in mechanical world is vibration. We all learn somewhat about mass spring damper systems, but when the problem becomes multivariable it gets hard. Derive equations for response analytically and understand them as well. Try to understand how m,d,k contribute to the response when you vary them. Play around it on matlab.

3)System Identification: This is also one of the most important aspects. No real system is given in a form G(s) as we deal with in theory. You have to model the system and then compare your model and identified system. If there is a possiblility in your study course attend such a lab, do a system id on a real hardware. Only then you can understand the problems that are there in real world (friction, saturation, instability for instance)

4)Actuators: In theory every actuator is perfect. No dynamics. But in real world, it has a bandwidth limited dynamics. It has a saturation. When you design a controller, check what kind of output it tries to set. If you have the possibility buy some kind of actuator and try to analyse its response. Do system ID and try to fit a transfer function to it. See its bandwidth, saturation etc.

5)Sensors: As well as actuators, sensors are also not perfect in the real world. They have a dynamic response as well. If you have a possibility buy some simple curcuit elements like a thermistor and try to build your own sensor. Look how its response looks. Try to calibrate it.

6)Frequency response: Frequency response analysis is quite relevant in our field. You almost always somehow have to check the system's frequency response. In Bachelor, take your time and learn the theory behind it well. Why a system with 1 pole and system with two poles behave like that? What does a resonance really mean in a physical world?

7)PID: PID is the first type of controller we all learn. It looks easy but there is always more to it. A PID in its generic form is not applicable on hardware because of D. Learn how you would implement a PID controller on C/C++ for instance. In industry noone is gonna ask you to implement MPC if you can solve it with a simple PID controller. Most of the Nonlinear MIMO Systems are controlled via Gain Scheduled Decoupled PID Controllers. What I want to mention is, do not skip it just because it looks simple.

8)State Estimators: There will almost always be a case where you cannot measure every state. In State Space this is almost always the case. So you have to implement a state estimator at some point. Begin with a simple Luenberger and then elaborate it to Kalman Filter types.

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To conclude, if you plan an industrial career, always be critical about the systems and theory you learn. Ofc some theory is there as we need fundemantals but in industry most of your work will be how to implement this and that. I wanted hereby to share my thoughts on things I wished I had known back then. Feel free to elaborate those points and correct me if you think I wrote sth wrong.

Hello Guys,

I graduated my Mechatronics Bachelor last Fall and started my MSEE at a Technical University right away. I have a strong interest in control of dynamic systems, specifically moving systems like robots, cars, planes/rockets. Topics that particularly interest me are humanoid robotics(like boston dynamics), Flight Control, GNC, ADAS or new robotics concepts. I have already passed my advanced control lecture and know that I want to purse a career (either academic/or industrial R&D) in control. I am currently visiting a lecture on advanced dynamics (numerical/multi-body). The professor was very confused on why I am visiting his lecture as a MSEE student. Given my reasoning above he suggested I switch to the "Theoretical Mechanical Engineering" Master program. I am seriously considering switching but I am still unsure, so I am asking here for advice.

The two masters programs both have the exact same control electives, but have different mandatory modules. See below.

MSEE mandatory: microwave engineering, microsystem engineering, power systems, digital communication

MSTME mandatory: FEM, numerics of ODEs, advanced dynamics (the lecture I am visiting right now), electives i find intersting: nonlinear dynamics, advanced robotics & multibody problems, flight mechanics

I could also do my MSEE and do the dynamics/mechanics lectures as extra credit. I do know that MSEE gives me more career range. The MSTME offers more opportunities for an exchange semester/year at highly prestigious universities, which I would also really like to do. I am just unsure how that aligns with my interests.

Hello, I've been studying basic control theory for the past 2 years as a part of my mechatronics degree I am doing for the army of my country.

I have found my self asking how to actually model any type of system, what's the approach?

I have no idea what the most simple example can even be, but let's say I have a heating system which just heats up a metal plate using convection, and a thermocouple reading off of it. The system is trying to stay at a certain degree by lower or up the amps/volts. (I think its volts) This is truly the simples I could think of, and totally theoretical, I don't have an actual system I am trying to figure out. I just want to understand how do I figure it out.

How do I take this information and figure out a model for this system and eventually doing a Laplace transformation for it to get it stable at the steady state?

Currently my professor is on leave, for idk how long.

Got any ideas? Advice? Resources for me to look for?

I want to specialise early

What books or papers do you recommend for presenting this control theory subject to an audience of mathematicians or graduate maths students?

Hello,

I'm in MS EE and have the following control and state estimation courses options. I am interested in career using control theory, state estimation, system identification for aerospace and biomedical devices.

From this list which courses which would you suggest as absolutely necessary for aerospace or devices?

Linear Systems, Stochastic Control, Optimal Control, Robust Control, Nonlinear Control.

Filtering for Stochastic Systems & Statistical Detection and Estimation.

Thanks.

Hello, I could spend an hour explaining how cooked my situation is, but I am going to spare you guys the time. Basically I am very stupid and want an easier, if not the easiest, control systems engineering book

Hello, nice to meet you. I'm an electronics student and I've been given this project: I have to physically control the water level in a plant with four tanks (see photo below), not just theoretically.

I've controlled a single tank before, but this is different. The problem is that the pumps are cross-connected: Pump 1 fills tanks 1 and 4, while Pump 2 fills tanks 2 and 3. Basically, if I adjust one pump to fix one level, I'll mess up the other. The details of the setup:

• The diagram follows ISA-5.1 standards.
• I have 4 LITs (Level) and 2 FITs (Flow) sending signals to a PLC.
• I use 2 Pumps driven by Variable Frequency Drives (SZ-01 and SZ-02). It's important to note that the water flow is controlled by adjusting the motor frequency via these VFDs.
• I have the freedom to add and program whatever blocks I want in the PLC :D.

You don't have to do the work for me, but if someone could guide me on which control structure would actually work for this tightly coupled system in a real PLC environment, it would be a huge help. Thanks!

https://preview.redd.it/2lwby2o7xmvg1.png?width=1160&format=png&auto=webp&s=2fbc633c60f9577215330a9f19981ffd1bef694f

Hi everyone, I’ve been working in aerospace for 3 years doing environmental control systems and mechanical systems design & analysis. I recently graduated from UW’s Masters in Aerospace Engineering program focussing in controls. I’m targeting a GNC&A roll in space systems. I didn’t opt to take the orbital mechanics elective, and i wish i had. Does anyone have recommendations on free coursework or reading?

I can handle some rigor but the purpose of this would be primarily preparing for interviews.

Hi everyone,

I’m working on a project involving tracking control of a six-DOF multi-axis coupled machine driven by electrohydraulic actuators.

At the moment, I already have a baseline control structure with a very good tracking accuracy. it comprises of an outer loop control and an inner loop control for the actuator side. What I want to do next is improve the actuator control law by adding an adaptive robust control term, based on a paper I’m referencing.

The problem is that the adaptive robust law in the paper is pretty computationally heavy, at least from the way it is presented mathematically, and I’m trying to figure out how people actually implement this in practice, especially in Simulink.

So I wanted to ask people who have worked on electrohydraulic servo systems or similar nonlinear actuator control problems:

When implementing adaptive robust control laws, do you usually build them using standard Simulink blocks?

Or do you normally put the heavy mathematics inside MATLAB Function blocks?

For parameter adaptation, projection laws, robust terms, pressure dynamics, valve flow nonlinearities, etc., what parts are usually done with blocks and what parts are better handled in code?

Are there practical tricks for reducing computational burden while keeping the controller faithful to the paper?

If you implemented something similar, what parameters or terms turned out to matter most in practice?

I’m especially interested in hearing from anyone who has implemented this on a real or realistic electrohydraulic servo model, not just in theory.

Thanks.

Hello,

I am implementing a full joint impedance controller on a factory robot arm (with feedforward coriolus, mass matrix, gravity comp, and friction comp). It works well, up to about 0.2 deg accuracy due to low gains (which I want) and static friction deadband. If I increase the coulomb friction compensation I introduce small high-frequency oscillations.

My ideas to solve this are either some secondary low amplitude damping term that allows me to increase friction comp and damp out its oscillations, or add some clipped/gated integral term. I was wondering if anyone has chased steady state error to ~0.01 deg and if either of my above ideas are standard in industry. Note I really just care about decreasing the error of my sensed versus realized joint angles, and I am not too concerned with hardware tolerances/physical accuracy. I more so just want my realized joint values to be within 0.01deg of my commanded, and I don’t want to increase my P gain. Any advice as to what’s happening under the hood on these sub-mm controllers would be greatly appreciated.

Say I want to design a PD controller to decrease the rise time by a factor of 2 while keeping the overshoot unchanged, I already know the value of damping ratio what is the quickest way to find wn?
Do I have to solve arc tan equations?? or if I am lucky substitute values into the characteristic equation?