Lost Secrets of the H-Bridge, Part I: Ripple Current in Inductive Loads

Jason Sachs July 8, 2013

So you think you know about H-bridges? They're something I mentioned in my last post about signal processing with Python.

Here we have a typical H-bridge with an inductive load. (Mmmmm ahhh! It's good to draw by hand every once in a while!) There are four power switches: QAH and QAL connecting node A to the DC link, and QBH and QBL connecting node B to the DC link. The load is connected between nodes A and B, and here is represented by an inductive load in series with something else. We...


Adventures in Signal Processing with Python

Jason Sachs June 23, 201311 comments

Author’s note: This article was originally called Adventures in Signal Processing with Python (MATLAB? We don’t need no stinkin' MATLAB!) — the allusion to The Treasure of the Sierra Madre has been removed, in deference to being a good neighbor to The MathWorks. While I don’t make it a secret of my dislike of many aspects of MATLAB — which I mention later in this article — I do hope they can improve their software and reduce the price. Please note this...


How to Estimate Encoder Velocity Without Making Stupid Mistakes: Part I

Jason Sachs December 27, 201230 comments

Here's a common problem: you have a quadrature encoder to measure the angular position of a motor, and you want to know both the position and the velocity. How do you do it? Some people do it poorly -- this article is how not to be one of them.

Well, first we need to get position. Quadrature encoders are incremental encoders, meaning they can only measure relative changes in position. They produce a pair of pulse trains, commonly called A and B, that look like...


Linear Regression with Evenly-Spaced Abscissae

Jason Sachs May 1, 20181 comment

What a boring title. I wish I could come up with something snazzier. One word I learned today is studentization, which is just the normalization of errors in a curve-fitting exercise by the sample standard deviation (e.g. point \( x_i \) is \( 0.3\hat{\sigma} \) from the best-fit linear curve, so \( \frac{x_i - \hat{x}_i}{\hat{\sigma}} = 0.3 \)) — Studentize me! would have been nice, but I couldn’t work it into the topic for today. Oh well.

I needed a little break from...


Tolerance Analysis

Jason Sachs May 31, 2020

Today we’re going to talk about tolerance analysis. This is a topic that I have danced around in several previous articles, but never really touched upon in its own right. The closest I’ve come is Margin Call, where I discussed several different techniques of determining design margin, and ran through some calculations to justify that it was safe to allow a certain amount of current through an IRFP260N MOSFET.

Tolerance analysis...


Debugging DSP code.

Mark Browne May 1, 2019

I am fascinated with neural network processing and have been playing with them since the 80's.

I am a frequent contributor to the Numenta forum. Numenta is the current project of Jeff Hawins, the guy that gave us the Palm Pilot. They are working with the HTM model. This is a system based on studies of the functions of the cortical column and has some very interesting properties: It processes sequential data streams and has very effective one shot learning. The data is arranged in Sparse...