pidtuner

7 ms·

31.
by pidtuner 6y ago
Fitting to sum of N exponentials is also a linear problem with no iterations https://math.stackexchange.com/questions/1428566/fit-sum-of-...
32.
by pidtuner 6y ago
Yes! Thank you Sir! I can see you know what you are talking about. This is my point, NNs are very useful for some problems, for others they are not worth the complexity and black-box nature.
33.
by pidtuner 6y ago
Polynomials are just an example, the easiest one. The point is that there are many more universal approximators (as some other user commented here), many of them much more suitable for control applications than NNs.
34.
by pidtuner 6y ago
In practice one computes (X^T * X)^-1 * (X^T) in one go using Singular Value Decomposition, for which very efficient algorithms exists. But if there is really a lot of data, then recursive linear least squares can be used, to partition the
35.
by pidtuner 6y ago
wavelets, sum of exponentials, fourier, ... I just mentioned polynomials because they are easiest. But people just jump into the NN bandwagon to get attention. Truth is that is just another tool, and a good engineer has to choose the best t
36.
by pidtuner 6y ago
For polynomial regression of the type y = p0 + p1 x + p2 x^2 + ... + pn x^n, the "training" algorithm is linear least squares (no need of gradient descent). Assuming you have data (y, x), the explicit least squares solution is P =
37.
by pidtuner 6y ago
The computational cost of "training" a polynomial would be the same as just one iteration of the training algorithm used by typical NNs. When it comes to trig functions, the story is the same as with the exp function e(). When you
38.
by pidtuner 6y ago
"The real promise of these methods is to use the universal approximator power of NNs...", still if one is to use a grey-box non-linear model dx/dt = F(x, u, t), why use NNs to characterize F? I would be more comfortable using
39.
by pidtuner 6y ago
I think you are right, in the case of the trebuchet, it just computes a black box approximation of the inverse of the system. The difference being that an analytic inversion would solve the problem for all wind and target conditions, while
40.
On how to tune a PID controller(forum.pidtuner.com)
3 points by pidtuner 6y ago|0 comments
41.
Show HN: Share Your PID Tuning to Cloud(youtu.be)
2 points by pidtuner 6y ago|0 comments
42.
by pidtuner 6y ago
Do you mean having individual sliders for each gain? Right now there is just one slider that scales all gains in such a way that unformily increases/decreases the closed loop bandwidth. You can try the tool with a simulator like https
43.
Ask HN: What Feature to Add Next
2 points by pidtuner 6y ago|3 comments
44.
Tune a PID in 6 Minutes(youtu.be)
2 points by pidtuner 6y ago|0 comments
45.
by pidtuner 6y ago
During my control studies, when talking about history, professors always use the centrifugal governor as a control application that triggered modern formal studies about control (basically discovering how useful it can be) https:/&#x2
46.
by pidtuner 6y ago
You can use https://pidtuner.com to obtain the gains based on an easy experiment
47.
by pidtuner 6y ago
As a control engineer and main developer of https://pidtuner.com , I never expected control theory to be widely used outside the industrial world (specially for solving certain CS problems)
48.
by pidtuner 7y ago
It is very easy to tune PID now a days with free tools like https://pidtuner.com
49.
by pidtuner 7y ago
You can use this Dockerfile to build Qt apps inside a container, which then can easily be integrated in any CI system: https://github.com/juangburgos/JenkinsCentOs7Docker/tree/mas...
50.
by pidtuner 7y ago
Mine is pidtuner.com, currently have 1000 engineers visiting each month. Not much, but quite specialized.
51.
Show HN: PID Tuning Using WebAssembly and Vue(pidtuner.com)
4 points by pidtuner 8y ago|0 comments