Pid tuning with a genetic algorithm
After the quadcopter pid thing about a month ago, I decided to try a genetic algorithm to tune the pid settings. This implementation is hella inefficient, I assume there is a better way to do it out there. It doesn't always converge to the same minimum, but, hey, variety is the spice of life.
Basically: Creates a number of possible pid settings through mutation and crossing over, then runs them against a quadcopter simulation, rated by time to stabilize and accuracy. Top two performers get bred together, repeating the cycle. If a particular pid setting fails to converge or takes too long, it is eliminated from the gene pool. If the population faces extinction, then a new population is created.
Feel free to tinker with the values in config.py.