First, since steppers are great at positioning (there is no need for a position feedback), you should certainly limit their movement as you've said yourself. I am not sure how the motor shaft is engineered right now, but if it was fixed to the motor, letting it continue spinning would risk damaging the equipment.
Next, 200ms transport delay in your sensor will probably be too slow, otherwise you will need to slow things down a lot in order to slow down the ball itself. Similar to what Rocket Surgeon said, you should simplify the image processing algorithm to calculate the path only once, and then quickly calculate only the position of the ball in each frame. If you want to skip this step quickly, find a red ball instead of this one, and then check only the red component in your RGB picture, until you've found a better algorithm.
For the PID control, start with the fact that you actually need two separate PID controllers, one for the east-west motor, the other one for the north-south one. If you have two exact motors, their parameters must be equal.
For a PID controller to act, it needs to know the error: difference between the desired position, and the actual position of the ball. X and Y components of this offset will be the inputs for two PID controllers (one for each motor). To get the error, you need to have the desired position on your path first: a trajectory.
To get the trajectory, you need to process the image and get the path, as well as its starting and ending point. I am not sure if your algorithm is capable of distinguishing the path from the rest of the board right now, but if not, note that this is an algorithm of its own to handle before continuing. Again, you can skip this part by manually entering the junction points, if you are eager to see some results quickly. In any case, you should be able to define the setpoint speed, and have your software move the desired coordinate position over the path, from start towards the end. Obviously, you will start with a low desired speed.
So, before starting with control, you should go through the following checklist first:
- Simplify your image processing algorithm to get faster response
- Create an algorithm which creates a trajectory over your path using a predefined speed
- In each frame:
- Calculate the difference between the trajectory and the ball position
- Pass the delta-X component to the east-west PID, pass the delta-Y to the north-south PID
It may turn out that it is better to create the trajectory one segment at a time, and continue with the next segment when that ball ends the previous one. Otherwise, you will need to take care that the ball doesn't overshoot the desired trajectory (which may be hard to accomplish)
(This question has been posted more than a year ago)
You need these angles in order to apply a control, a PID for example, to stabilize the quadcopter in hovering mode. Your control is supposed to be active when you are not remote controlling your drone and you want it to be perfectly horizontal. This means that the theta(x axis) and phi(y axis) angles will be close to zero and will reach the desired reference value ( =0 ) thanks to the control.
I have a question for you: Have you recorded these values while the motors were spinning? I've noticed an important increase in noise amplitude caused by vibrations on the chassis.
Best Answer
PID isn't a magic tool to accomplish all tasks, rather an universal method of control. Your oscillations are probably due to too much high Kp setting. Probably your control loop is missing some trivial part which is feedforward control path that would help a lot.
The picture below is representing a static characteristics where two world differ: the closed loop control theory (ger. Regulierung) and open loop theory (ger. Steuerung) The small letters refer to closed loop, which is superimposed on static characteristics in the working point.
These two worlds can be combined together by means of feedforward control path. The closed loop is trying to reject the disturbance, while the feedforward path is injected to the output of the controller. This feedforward path could be a static value as well dynamically changing value. For example if you know the speed of the copter blades "a priori" then you can fed this information right at the output. This would now be your working point as depicted in above characteristics.