So, when playing around with setpoints, I find that my error integral gets wound up to a large value in that it dominates everything else. While working out the problem, I have been running on PD mode (Setting K_i to zero).
Trying to find a better solution I hit up Wikipedia: http://en.wikipedia.org/wiki/Integral_windup
When I read the fourth solution: 'Preventing the integral term from accumulating above or below pre-determined bounds', I wondered why one of the preferred methods for controlling windup is to have the integral computed over a rolling time window.
Say you have an additional parameter, that instead of going from t=0 you start Now - Parameter seconds/minutes ago and add up all the discrete error. To me this is pretty intuitive although I am hesitant because I can't seem to find any whitepapers/websites that talk about the idea.
So for the process engineers out there, why do we set an absolute deviation on the integral instead of just time truncating it?
Trying to find a better solution I hit up Wikipedia: http://en.wikipedia.org/wiki/Integral_windup
When I read the fourth solution: 'Preventing the integral term from accumulating above or below pre-determined bounds', I wondered why one of the preferred methods for controlling windup is to have the integral computed over a rolling time window.
Say you have an additional parameter, that instead of going from t=0 you start Now - Parameter seconds/minutes ago and add up all the discrete error. To me this is pretty intuitive although I am hesitant because I can't seem to find any whitepapers/websites that talk about the idea.
So for the process engineers out there, why do we set an absolute deviation on the integral instead of just time truncating it?