Implementing Traction Control for an advantage in the 2009 game

[agmlego]

Our team is looking into implementing an algorithm we found for a four-independent-wheel-drive electric vehicle ETS, using four encoders and a gyroscopic yaw-rate sensor. We will be enhancing it with the accelerometer to detect sideways skid and report to the driver, if not correct it.

[EricS-Team180]

Originally Posted by agmlego

Our team is looking into implementing an algorithm we found for a four-independent-wheel-drive electric vehicle ETS, using four encoders and a gyroscopic yaw-rate sensor. We will be enhancing it with the accelerometer to detect sideways skid and report to the driver, if not correct it.

Right now Warren B and I are trying to get our arms around Paul's "middle income" solution. But for those of you going for the "super rich" solution, I have found a few interesting places to look:

http://scholar.lib.vt.edu/theses/ava...ed/Thesis2.pdf

and here's some observer and alpha-beta filter explanations:

http://www.mstarlabs.com/control.html


Check out "rough Data, Smooth signals" and "When One feedback isn't enough"

I expect SPAM'll compete with the "middle income" solution at the Florida regional

cool stuff
Eric

[agmlego]

Hey, cool! I will definitely have the guys look in on those.

[Bongle]

Just a note:
We went to implement our accelerometer/encoder solution last night, and it wasn't as good as expected. This was partly because I hadn't totally thought it through and thought that simply comparing accelerations was going to be sufficient. I failed to realize the obvious fact that the encoder acceleration would not STAY above the accelerometer acceleration for long, so it is not a good way of telling when the wheelspin stopped. It was an excellent way of telling when your wheel started spinning, but since you can't easily detect when they stop spinning, the algorithm as I described it is not ideal.

We're going to have to get a bit more complicated, with either an estimated velocity from the accelerometer or a trailing wheel to get this working properly.

[Jared Russell]

You can try integrating the acceleration signal to get velocity, and then comparing velocities to detect slip. The problem is that a noisy accelerometer signal looks even worse once it's integrated. For this and other reasons (one being the simplicity of an apples to apples speed comparison in code), non-driven encoder wheels lead to a better solution to this problem in my opinion.

[Bongle]

Originally Posted by Abwehr

You can try integrating the acceleration signal to get velocity, and then comparing velocities to detect slip. The problem is that a noisy accelerometer signal looks even worse once it's integrated. For this and other reasons (one being the simplicity of an apples to apples speed comparison in code), non-driven encoder wheels lead to a better solution to this problem in my opinion.

Yeah, that's exactly what I'm thinking. Even with our rolling-average filtering, the accelerometer is ridiculously noisy.

[Rickertsen2]

Originally Posted by cgredalertcc

My final thought:

If the problem we face is that Traction=Normal Force * Coefficient of friction, and we have now way to increase our coefficient of friction why not increase the normal force? Last year 1741 used a very small vacuum to great effect in capturing balls. Why not apply the same idea to a robot? The area of the robot (28 x 38) is 1064 square inches if even 1/2 psi vacuum is applied to that area that is over 500 pounds of downward force. I know Bill has said that he doesn't like this idea, but he didn't like the idea of launchers last year, and look how many teams did that.

p.s. I know that last part isn't really traction control but its an idea I had that I wanted to throw out there. I guess the thought was who needs traction control if you aren't lacking traction.

Sounds like the legendary 1978 Brabam BT46B Formula 1 car which used an enormous fan underneath to generate a vacuum and more normal force. The car won the one race it ever competed in but was declared illegal

[Joe Ross]

Originally Posted by Bongle

Yeah, that's exactly what I'm thinking. Even with our rolling-average filtering, the accelerometer is ridiculously noisy.

We were given a +/-3g accelerometer, and our robots can accelerate at around +/- .05g (based on the published COF). Therefore, we can only use a ridiculously small portion of the range of the ADC.