Automatic PID tuning: an application of unfalsified control

In this paper, we give detailed procedures for using unfalsified control theory for real-time PID controller parameter tuning and adaptation. Related to the candidate-elimination algorithms of machine learning, our PID tuning technique does not need a plant model and makes PID gain selection possible by just using observed data. Simulation results are included.