Towards explicit PID control tuning using machine learning

The PID control algorithm is the most used industrial control method owing to its simplicity and ease of use. However, tuning PID parameters is not trivial and many methods have been reported in literature. This paper seeks to show a machine learning approach using multivariate regression with gradient descent and the normal equation. The first order cruise control system is used as an example and results show good progress towards automatic PID tuning using learned data.