Title :
Automatic PID tuning: an application of unfalsified control
Author :
Jun, Myungsoo ; Safonov, Michael G.
Author_Institution :
Dept. of Electr. Eng. Syst., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
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
Keywords :
adaptive control; control system synthesis; real-time systems; three-term control; tuning; adaptation; automatic PID tuning; candidate-elimination algorithms; gain selection; machine learning; observed data; parameter tuning; real-time PID controller; simulation results; unfalsified control; Adaptive control; Automatic control; Control systems; Control theory; Extraterrestrial measurements; Feedback loop; Machine learning; Machine learning algorithms; Three-term control; Tuning;
Conference_Titel :
Computer Aided Control System Design, 1999. Proceedings of the 1999 IEEE International Symposium on
Conference_Location :
Kohala Coast, HI
Print_ISBN :
0-7803-5500-8
DOI :
10.1109/CACSD.1999.808669
