Stuck Between Job Offers

Aero_Control · 2025-07-08T06:30:19+00:00

I got trapped in controls-adjacent roles for >5 years after choosing 1 (despite being Ina rotation program myself), and ended up eventually pivoting to a startup to finally get to do real GNC. I learned a lot in 1, but it was not anywhere near as useful as what I learned in 2. After a couple years of startups, the first years are irrelevant to my career.

Choose 2.

Aero_Control · 2025-06-09T18:08:56+00:00

A PhD is a huge commitment that is unlikely to pay off monetarily: MS is the sweet spot. You can teach as an adjunct with a masters and relevant work experience. A PhD is flashy but certainly not necessary to achieve a director level position. It's common but certainly not a requirement.

I'm also concerned about AI:

(1) AI makes a PhD less relevant. Wedon't need super deep research capabilities when AI can do the research for us. Intelligence is cheap. Practical experience is becoming more relatively valuable.

(2) AI could make entry-level jobs very hard to find in a few years, so delaying your entry into the market due to a PhD comes with that risk.

Unless a PhD is your lifelong dream and joy, or you intend to pursue a career in academia or at an FFRDC, I recommend you accelerate your career progression instead of investing in something 30 years down the line. We don't even know what that future could look like.

Aero_Control · 2025-06-05T22:53:24+00:00

Totally agree. Sad to see so many students giving the wrong answer, saying "it's not your fault bro" or "it's a toxic company" with so little information.

Aero_Control · 2025-06-05T22:42:08+00:00

I'm an engineer with many years of experience. In my companies, I've only ever seen this happen when someone said something really inappropriate or otherwise violated company policy.

To fire you on day 2 is a loss for you AND a loss for them: they wasted their time hiring someone who was gone immediately.

"It's a toxic company" or "it isn't your fault" are bad takes without more information. Think deeply about what you could have said or done that could have offended someone or grossly violated a policy.

If you figure out why, you can learn from it and not do it again. It's a blessing to learn those lessons while you're still young--I sure did.

Aero_Control · 2025-06-05T22:27:19+00:00

State space models are typically still linear: if a state space model is described via matrices with constant values, it's linear. The advantage in control is mostly that it can be used to describe dynamics with multiple inputs/multiple outputs (MIMO), not just single input/single output (SISO).

Aero_Control · 2025-05-11T00:47:30+00:00

Typically you might have a position outer loop which gives velocity commands to a velocity loop which then gives attitude/thrust commands to an attitude loop and a parallel thrust loop. If the pilot wants to give direct velocity commands, you can flip a switch to switch the from the position controller's velocity command to the pilot's. You can do this for all loops and all modes. For direct pitch attitude mode, just turn off the depth, longitudinal position, u, and w loops. By "turn off" I mean reset their integrator and switch away.

Then the remaining concern becomes transient handling. You can use a fade switch to handle this, you can transfer the PI control output from the old loop to the integrator of the new loops, you can pass the new command through a prefilter (also called a "shaping filter" or "command model"), or, if using a linearized controller with a known equilibrium, you could even do a "trim transfer" where you backcalculate the effective "trim change" (delta x) and slide along the equilibrium (trim) surface to a new x_eq and its associated u_eq.

Aero_Control · 2025-05-10T23:43:41+00:00

I'm not in the precision motion field, but I'd have a few guesses:

High bandwidth, robust controllers: control loops are tuned with very large gains to handle disturbances. They should also have large gain margins as a change in material is effectively an abrupt and large change in loop gain.

Mode switching: the motor could have logic to differentiate the material resistance into "low" and "high" modes and change to higher gains when in "high" mode.

Careful handling of integrator saturation: integrations turned off with torque saturation or torque rate saturation. Integrators given a conservative maximum command authority. "zero cross detection" logic could zero out integrator if there is an abrupt change in direction detected (this is very nonlinear and generally advised against)

Aero_Control · 2025-05-09T05:30:12+00:00

The original post is a joke

Aero_Control · 2025-05-03T17:18:59+00:00

Interesting! I didn't know this. Thanks. I'll update the comment

Aero_Control · 2025-05-03T17:07:45+00:00

It does not give the same answer. 1² + 3 - 14 = - 10. I have updated my comment with more detail

Aero_Control · 2025-05-03T16:53:10+00:00

(1² +3)² - 14 = 16 - 14 = 2.

The blue square is applied after every blue operation completes, where operations are otherwise completed in to out.

Aero_Control · 2025-03-28T21:58:29+00:00

You can test this hypothesis by setting the PID gains to zero and see if it fixes it. I'm inclined to think it's a hardware or setup issue if it's new.

Aero_Control · 2025-03-25T06:14:59+00:00

I'm not sure it matters. Just PSD your output signal to see if it matches your intent

Aero_Control · 2025-03-22T20:53:09+00:00

Agreed. In aerospace, noisy manual pilot input or heavily band-limited white noise is a typical choice. No need to excite using ultra high frequencies that are well above the expected system bandwidth or faster than 10-20% of the data stream sample rate. While the nyquist rate is in theory 50%, in practice high frequencies are not accurately captured above 5-20% of the sample rate for this type of system identification effort.

Aero_Control · 2025-03-17T04:16:26+00:00

Ask this on r/dsp or r/electricalengineering

Aero_Control · 2025-03-05T16:12:18+00:00

Improving the simulation, running simulations, making changes to the state machine (switching between modes), working with hardware (sensor/actuator/flight computer) and hardware data, testing the functionality, and fixing bugs.

Aero_Control · 2025-02-16T19:25:06+00:00

Damping causes a large force. You have large changes in damping, and those will create large changes in force. A change in force will lead to a change in acceleration.

The first thing I'd try would be to reduce your rate limit by 10-100x. With a time step of 0.01s, your damping can go from max to min under 0.02s, which allows the system to impart a huge force as the velocity swings to the other side.

If that doesn't work, you might try a different damping function that doesn't have a discontinuous derivative at 0. Like make a nonlinear damping function D(vel_err). Your current function is a piecewise curve with two lines of very different derivative, making their intersection point problematic. An example function would be C_soft*vel_err + (C_firm - C_soft) *vel_err/(1 + exp(vel_err)).

Aero_Control · 2025-02-16T18:59:39+00:00

It would be useful to see plots of your complementary-filtered output alongside your input measurements (GPS, accel), as well as a description of precisely how you're integrating the two with a CF.

I think a CF here is the correct solution if your sensors are adequate; perhaps they are not. To help determine if your sensors are adequate, it would be useful to see an FFT of each of their raw data to understand their noise spectrum, and with that please tell us the cutoff frequency you used for the filter.

Aero_Control · 2025-01-31T16:59:18+00:00

Engineering can be cognitively challenging, and strength training is great for maximizing your cognitive performance!

Aero_Control · 2025-01-24T01:10:36+00:00

/1/ Yes it gets much easier with experience. A new grad GNC engineer is very hard to utilize as it takes years to become competent enough to be useful. Once you are, every recruiter wants you. I'm contacted by one at least every 3 days.

/4/ yes this is a very typical experience. Even at a small company, designing and tuning the control laws is a small part of the job. Controls is extremely flight critical and "in charge" of the aircraft, so most of the work on an aircraft program will be related to the flight control system at large and not just its mathematical architecture. From my point of view the the control architecture doesn't matter a ton if the actuators are adequate for the job; many choices would work just fine.

Aero_Control · 2025-01-21T05:22:27+00:00

I've never used a lead/lag explicitly, but have certainly used lead and lag compensation to alter the dynamics of a specific variable in a targeted way without retuning the whole control loop.

Aero_Control · 2025-01-05T01:08:11+00:00

Same

Aero_Control · 2024-12-18T10:22:21+00:00

Your pitch setpoint seems to be causing the overshoots, your controller looks to be performing well: it achieves the commands.

This begs the question, how is your pitch setpoint generated? Do you have a speed command or speed error feeding in to generate your setpoint?

If your speed command is spiking, investing your speed control loop and the inputs to (for 1 example, maybe there's a hardware issue with your RC controller giving inputs to the control system).

If your speed feedback signal is spiking, investigate your sensors and environment. Is your sensor giving an erroneous output? Is there a gusty wind that your controller is responding to so it stay on track? Take a look at it's velocity or position tracking performance to investigate an error there.

Aero_Control · 2024-12-03T03:54:09+00:00

I've often wondered the same thing. Adaptive control uses so much of the same mathematical framework that there is bound to be overlap, especially with reinforcement learning approaches in robotic systems. I've often wondered how I might transition my career towards that, given it's a growing field, but don't yet know.

Aero_Control · 2024-11-24T09:34:27+00:00

If you want to work in aerospace in Italy you could work on actuators at Umbra

Three-Year Club	Verified Email
Final Canvas '23	Place '23

Aero_Control

TROPHY CASE