Hi, my name is Ralf Gerlich!
A graduated computer scientist by trade and a formal methods guy I like to get to the bottom of almost all things technical and mathematical – and sometimes I take my time exploring side-tracks in detail before moving on.
My unfocused focus is on embedded systems, electronics and avionics, with sides from physics, control theory and statistics. My interest is in getting a good understanding of things: More than just walking well-trodden paths, but also becoming able to leave the walkway for a while and dwell in the shrubs or on the shoulders, and from time to time lift a stone and look at what’s beneath it.
And then I love sharing what I found…

Generating normally distributed random values using SciPy is easy. However, how can you generate “normally” -distributed values with a skew? It’s got to do with boxes, and going down that rabbit hole gives us some insight into normal distributions as well.
Maxwell’s Equations can be used to determine electric and magnetic fields, which are important for machines using them for work, such as electrical motors. I want to share a few insights and videos on the topic with you.
Ever wondered how a wing generates lift? We’ll find out and have a look into how lift relates to velocity, air density and the area of the wing.
We take a look at a powerful tool for modelling, the Buckingham Pi Theorem, and use it to extrapolate from the performance of one DC motor to another.
We derive the minimum number of measurements we need to properly identify a system using OKID by looking at the ranks of the involved matrices and considering oversampling.
The Observer/Kalman Identification Procedure can be used in conjunction with the Eigensystem Realisation Algorithm to identify the parameters of a linear, time-invariant system from general measurement data. Again, we delve into the depths of its derivation and see the tricks its inventors used to get the solution.
The Eigensystem Realisation Algorithm allows us to identify the parameters of a linear, time-invariant system from impulse-response measurements. We take a deeper look at the derivation of the algorithm and the tricks its inventors used to come up with the solutions.