When operating a moteus controller with a brushless motor there are two main things that can get hot: the FETs (field effect transistors) on moteus and the motor itself. By default, moteus has built in thermal throttling and fault detection if the FET temperature exceeds rated limits. In many configurations, the motor can be thermally connected to the moteus controller, so that the same FET temperature sensing can be used to prevent damage to the motor, but that isn’t always the case.

We’ve got a new firmware release for the moteus controllers up on github now, 2024-10-29! This update has a few new capabilities, a brief summary is below, while more detailed posts will come in the not too distant future:

MA600 Support: The MA600 from Monolithic Power Systems is an absolute magnetic encoder that uses a TMR (precision tunnel magnetoresistance) sensor. It is much more accurate with less noise than the AS5047P that moteus uses (or the MA732).

TLDR: As of firmware release 2024-05-20 moteus can now report a pretty good estimate of the electrical (and thus mechanical) output power going to the motor. You can get that through all the language binding options or in tview!

Background

Brushless motor controllers like moteus act like step down DC/DC converters. Their input is a higher voltage and low current, while the output to the motor is low voltage and higher current. If working properly, the output current is driven so as to produce torque at the output shaft.

I made a thing!

With that video out of the way, here is a bit more of a write-up!

Motivation

The hoverbot is a simple 2 wheel balancing robot. I built it to demonstrate how the moteus-c1 can be used to drive hoverboard motors and to demonstrate the capabilities of the pi3hat for high rate control and effective attitude reference calculation. It is powered by a single Bosch 18V cordless drill battery and controlled through an identical websocket based interface as the quad A1, primarily operated by a phone with a paired bluetooth joystick.

As of pypi 0.3.68, tview has gained the ability to delay execution of a compound command until the currently executing trajectory is complete. This can be useful for developing more complex motions that consist of multiple steps.

To use it, just issue a '?[optional_id]' in your command sequence. For instance, to move to position 1 and come to a stop, then move to position 0 when that has completed, you could do:

When setting up a moteus controller with a new motor, you typically first run the automatic calibration sequence as documented in the reference manual. When your system is working well, that should be all that is necessary to enable moteus to perform accurate FOC based torque control of the motor. Then you can set up basic parameters and tune the position PID control loop. What happens though when the automatic calibration doesn’t work? This post shares the most common failure modes during calibration.

Probably one of the most frequently asked questions in the mjbots Discord is “how fast can I send new commands to moteus”, or “how fast can I read the status from moteus”. That may be because you want to perform torque based control in your application and require high bandwidth, or just because you have a high torque to inertia ratio system that reacts on very short time-scales. No matter the reason, the principles that control the maximum rate you can send updates are the same.

I’m excited to announce the newest addition to the moteus line of BLDC controllers, the moteus-c1! The moteus-c1 is a smaller, lower power, lower cost version of the moteus-r4 and moteus-n1, but still packs a big punch.

The top of the line performance metrics for the entire moteus lineup now look like:

The upshot is that for low current motors where RS422 is not required, it is nearly as capable as the moteus-n1 for less than half the price!

The moteus line of brushless motor controllers currently require a CAN-FD host to send commands in order to actually execute a motion profile. moteus has long provided a python library that can be used on desktop operating systems to send commands and parse responses, and recently added a C++ one as well. Next up, and described in this post, is a library for Arduino which provides the ability to command and monitor brushless motors using moteus motor controllers.

Recently I covered a new feature for the moteus brushless controller that improved robustness for velocity control when external torques exceed the maximum allowable control torque. In this post, I’ll cover a feature that can be used for a similar situation in position control, “recapturing position and velocity”.

In some applications, while in position mode, it can make sense to limit the maximum torque during specific periods so that external torques are able to overpower the controller. The most obvious case would be if the maximum torque is set to 0, or the kp and kd scale are set to 0 temporarily. A problem then arises when resuming control, as the “control position” will be wherever it last was, despite the fact that the actual motor have have been dragged by the external torque some distance away. When the torque limit is released, a large transient can develop as the controller tries to instantaneously get back to the old control position.