The LM3x series of sensors are precision, easily-calibrated, integrated circuit temperature sensors. These are ideal as a beginner sensor, only to disappoint when code is copied from somewhere, run on the MCU and the temperature readings seem to be wildly varying and incorrect. Why is this happening and what can be done about it? Read on.
Once I started using rotary encoders to provide a ‘modern’ user input experience, the elimination of panel mounted potentiometers for circuit settings and other adjustments was the next logical step. Panel mounted pots have a very different feel from the clicks of a rotary encoder, and potentiometers cannot easily be controlled by a microcontroller.
Digital Potentiometers perform the same functions as mechanical pots but can be automated. So how do they work?
I was exploring ways to make a future robot project more appealing and came across a number of articles about animated robotic eyes created to convey expression or mood. This looked like a bit of fun and quite achievable using the LED matrix modules that I have been playing with for a while. Here’s the result.
In Part 1 I described the hardware components and the functionality of the LED clock. This this part, I’ll explore the software required to implement the functionality and seamlessly manage the different user interfaces.
I wanted a create a simple project to test a few ideas and still be useful in its own right. Walking through my local IKEA store, I saw a really inexpensive analog clock (Rusch) and decided that it would provide the right vehicle for what I had in mind.
A logic analyzer is an electronic instrument that captures and displays multiple signals from a digital system or circuit on a common time base. It is a really useful tool for debugging circuits and communications links. However, the cost of brand-name logic analyzers runs into hundreds of dollars and can be really hard to justify for hobby use.
Fortunately, there is a low cost alternative using open source software and inexpensive hardware.
In the first part of this blog I described building a test apparatus that allows me to experiment with tuning a PID loop controlling a levitating pin pong ball in a tube.
This second installment is about trying different hands-on methods of tuning the loop, understanding how they are derived, and how well they perform compared to each other.
PID (Proportional, Integral, Derivative) control is a classic control algorithm that I have used for a few projects, ending with ‘good enough’ control, without really spending time learning how to properly tune the PID constants.
Time for me to fill in the gap in my knowledge, so in this two part blog I want to capture my learning. Hopefully it is useful for someone else. In this first part I will document the learning and testing rig and software. The next part will be about tuning the control loop.
In some upcoming projects I intend to embed some processing intelligence into small devices. The smaller Arduino boards are too big and expensive for these applications.
After some investigation, I settled on using the ATTiny series of 8 pin microcontrollers. These processors vary in capability (from a very low end) and all provide 6 I/O ports. Tools compatible with the Arduino ecosystem are also available.
As a first step, I designed a small breakout board for the SOP8 version of these MCUs.
I always seemed to get a clash between the device select signal (SS) on my SD/microSD card reader and some other Arduino hardware I was trying to run with it. To get around this I decided to make a dedicated SD card shield with a jumper selectable SS signal.
SS signal clashes are now a thing of the past!