Sorry for the provocative and somewhat pointed question. It is no secret that the general population's appreciation of the "hidden technology" is almost zilch. The employer/industry sectors are even worse outside of a few corporations (and half are in aerospace apparently). There are many many skills/knowledge nowadays that are favored way more than control knowledge. The gap between control theory and practical engineering seems to be ever present and increasing in many domains.

I have wondered whether this is because control theory abstracted itself way too much and became somewhat inapplicable to everybody out there.

I was reading an old control theorist's biography and the person said what attracted him to the field was that a car engine can be represented as a transfer function. And you can represent a chain of system as composition of transfer functions. Then you can throw the entire toolbox of linear algebra and complex analysis at it.

Yet, this way of doing things is not the dominant engineering paradigm. While there is a lot of simulation involved in the design of many engineering systems, and I have this feeling that treating everything as transfer function is probably not going to cut it in the real world.

Now I wonder how it became this way. Is it so that control theory becomes easier to teach and attract students? Or perhaps it is easier to treat mathematically, thus easier to write papers about?? What is your take?

I'm working on autonomous quadrotor navigation using a 13-state NMPC (acados) with HOCBF-based obstacle avoidance.

I'm observing an issue where the drone approaches an obstacle, suddenly commands near-zero thrust, makes aggressive corrections, and starts oscillating back and forth near the obstacle boundary.

The logs show that HOCBF sometimes modifies the nominal NMPC commands, but near-zero thrust also occurs when both solvers report success. I've also observed actuator saturation, occasional solver failures, and differences between commanded and applied controls.

I'm trying to understand whether this behaviour originates from the NMPC optimization, HOCBF constraint activation, model mismatch, or interactions between the controllers.

Has anyone encountered similar behaviour with NMPC-CBF architectures? What would be a systematic mathematical approach to identifying the root cause rather than tuning parameters through trial and error?

I'd appreciate any insights or pointers to relevant literature.