The tuning of Proportional-Integral-Derivative (PID) can be considered a mix of art and science. It's an art where one needs to use their judgment and experience to understand the controller’s behavior. The science of tuning comes into the picture where one uses open-loop mathematical models and different techniques to derive the tuning parameters. The “Art” of tuning helps to understand the how’s and why’s of the process, and the “Science” of tuning provides a roadmap for tuning.

The performance of any PID controller depends on tuning parameters, i.e., gain, integral time, and derivative time that is set in. The tuning parameters are a function of process types, functionality expected from the PID loop, i.e., variance reduction or setpoint tracking, and type of the PID loop.