2019-07-09, 12:54 PM
I think you are right. The obvious parameters in order:
1) apparent wind angle
2) boat water speed
3) apparent wind speed
4) seastate
Each parameter adds a dimension, so likely the gains would have to be interpolated often since new states would be found often.
The autogain.py is nothing more than a hack. It tries certain gains and a search space and logs the course error and power consumption for each setting.
Surprisingly the gains can vary over a relatively large range and still give good performance in light conditions. This works but it's a very slow way to find the best gains. By the time it does (up to an hour) usually conditions already changed.
I intend to use neural networks to provide the smartest autopilot. This means that it doesn't just steer well but learns fast. It can also use many types of input sensors together including cameras looking at waves.
1) apparent wind angle
2) boat water speed
3) apparent wind speed
4) seastate
Each parameter adds a dimension, so likely the gains would have to be interpolated often since new states would be found often.
The autogain.py is nothing more than a hack. It tries certain gains and a search space and logs the course error and power consumption for each setting.
Surprisingly the gains can vary over a relatively large range and still give good performance in light conditions. This works but it's a very slow way to find the best gains. By the time it does (up to an hour) usually conditions already changed.
I intend to use neural networks to provide the smartest autopilot. This means that it doesn't just steer well but learns fast. It can also use many types of input sensors together including cameras looking at waves.