Title :
The auto-tuning PID controller using the parameter estimation
Author :
Cha, Inhyuk ; Han, Changsoo
Author_Institution :
Dept. of Mech. Eng., Hanyang Univ., Seoul, South Korea
Abstract :
This paper suggests an improved PID control algorithm, which could adjust the control gains automatically. The extended Kalman filter (EKF) which based on the singular value decomposition (SVD) is used for the estimation of an unknown or a time-varying parameter: The EKF is being used as an observer and the control gains are tuned through it. A controller using the EKF has the advantages that the EKF works as an observer and noise filter concurrently The performance of a proposed control algorithm is verified through the simulation and experiment with a servo motor system. The suggested controller will be useful in tracking control of a system with time-varying or unknown parameters
Keywords :
Kalman filters; adaptive control; filtering theory; noise; observers; parameter estimation; self-adjusting systems; singular value decomposition; three-term control; EKF; SVD; auto-tuning PID controller; extended Kalman filter; noise filter; observer; servo motor system; singular value decomposition; time-varying parameter estimation; tracking control; unknown parameter estimation; Automatic control; Control systems; Induction motors; Kalman filters; Parameter estimation; Process control; Servomotors; Singular value decomposition; Three-term control; Time varying systems;
Conference_Titel :
Intelligent Robots and Systems, 1999. IROS '99. Proceedings. 1999 IEEE/RSJ International Conference on
Conference_Location :
Kyongju
Print_ISBN :
0-7803-5184-3
DOI :
10.1109/IROS.1999.812979