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Lesson-5.markdown
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......@@ -161,9 +161,9 @@ Due to our results from experimenting with the color sensor in lesson 1 we also
### Results
The initial test with random control parameters showed by inspection that also for this robot construction and color sensor that the clean white surface was the best of the three. According the surrounding light we exprirenced a significantly difference between natural light and artificial light where the robot performed much better when surrounded by artificial light.
The initial test with random control parameters showed by inspection that also for this robot construction and color sensor that the clean white surface was the best of the three. Regarding the surrounding light we experienced a significantly difference between natural light and artificial light where the robot performed much better when surrounded by artificial light.
In order to find the most suitable control parameters the robot is placed on the white surface in a room only lit by artificial light and then the same procedure as in exercise 1 is followed. Starting out setting `Kp`, `Ki` and `Kd` to 0 and then adjusting one paramter at a time through the PC GUI.
In order to find the most suitable control parameters the robot is placed on the white surface in a room only lit by artificial light and then the same procedure as in exercise 1 is followed. Starting out by setting `Kp`, `Ki` and `Kd` to 0 and then adjusting one parameter at a time through the PC GUI.
By doing this procedure for each parameter we ended up with the following estimate of the best possible setting of the control parameters
......@@ -312,9 +312,15 @@ Other similar tests could be performed to test how the environment(temperature,
To test the robot and the different gains effect on the robot, as described in the setup, we tried to control the robot with one gain at a time:
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* **KGyroAngle**: Controlling the robot only with the gyro angle, was not possible. The problem encountered was that the angle drifted with time. In the beginning of the test, the angle was correctly 0 degrees when the robot was in an upright position, but during the test this changed to +5-10 degrees. This meant that the robot tried to maintain a position which was not upright, and therefore fell over.
* **KGyroSpeed**: The gyro speed did not drift in the same way as the angle and as a consequent the control using only the gyro speed was much better than the angle, although it was not sufficient for the robot to maintain balance. Since this term becomes non-zero fast when the robot is falling, it causes the control to act faster than relying on the angle alone does.
* **KSpeed**: The motor speed gain determines the resistance in the motor. The faster the wheel was spanned, the higher the resistance from the motor.
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* **KGyroAngle**: Controlling the robot only with the gyro angle, was not possible. The problem encountered was that the angle drifted with time. In the beginning of the test, the angle was correctly 0 degrees when the robot was in an upright position, but during the test this changed to +5-10 degrees. This meant that the robot tried to maintain a position which was not upright, and therefore fell over.
* **KGyroSpeed**: The gyro speed did not drift in the same way as the angle and as a consequent the control using only the gyro speed was much better than the angle, although it was not sufficient for the robot to maintain balance.
* **KSpeed**: The motor speed gain determines the resistance in the motor. The faster the wheel was spun, the higher the resistance from the motor.
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* **KPos**: The motor position gain makes the wheel turn back to its original position. Increasing the gain increases the speed with which the motor turns back to the set-point. If increased to much, the motors starts oscillating.
A possible cause for the erroneous angle could be, that the gyro sensor is more sensitive in the forward direction than backwards, causing a small error on each gyrospeed calculation, which the integration over time then accumulates.
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