Quote:
Originally Posted by AustinSchuh
Model based control is required  Once you get the hang of it, I find it to let us do cooler stuff than non-model based controls. We plot things and try to figure out which terms have errors in them to help debug it.
The states are:
[shoulder position; shoulder velocity; shooter position (relative to the base), shooter velocity (relative to the base), shoulder voltage error, shooter voltage error]
The shooter is connected to the superstructure, but there is a coordinate transformation to have the states be relative to the ground. This gives us better control over what we actually care about.
The voltage errors are what we use instead of integral control. This lets the kalman filter learn the difference between what the motor is being asked to do and what actually is achieved, and lets us compensate for it. If you work the math out volts -> force. |
First of all your robot is truly amazing!
I have a few questions about your control.
1.I have read about your delta-u controller and I am not sure if I understood it correctly and I would like to know if i got it right. You have 3 states on your state space controller which include position , velocity and error voltage. you model it as (dx/dt) = Ax + Bu and u is the rate of change of voltage. Then you use pole placement to find the K matrix and then in your controller you set u to be -Kx. Then you estimate the state from position using an observer. you use an integrator for u and command the motors with it. To the error voltage state you feed in the difference between the estimated voltage from the observer and the integrated u commands.
2.Will the delta-u controller work the same if i will command the motors with u and not the integral of it and instead use the integral voltage error as state? why did you choose this way for the controller and not another form?
3.Is the delta-u controller in the end a linear combination of position error, velocity error and voltage error?
4.Why did you use Kalman filter instead of a regular observer? How much better was it in comparison to a regular observer?
5.How did you tune the Q and R matrices in the kalman filter?
6.How do you tune the parameters that transfrom the motion profile to the feed-forward you can feed to your motors?
7.How did you create 2 dimensional trajectories for your robot during auto?
8.How do you sync multiple trajectories in the auto period? for example how did you make the arm of your robot go up after crossing a defense?
Thank you very much!