Title :
Stabilization of double inverted pendulum with self-tuning neuro-PID
Author :
Fujinaka, Tom ; Kishida, Yoshiyuki ; Yoshioka, Michifumi ; Omatu, Sigeru
Author_Institution :
Dept. of Comput. & Syst. Sci., Osaka Prefecture Univ., Japan
Abstract :
A self-tuning neuro-PID control architecture is proposed and applied to the stabilization of double inverted pendulum. The gain parameters of the PID controller are tuned using a neural network. The effectiveness of the proposed method is shown through simulation and experiment
Keywords :
intelligent control; neurocontrollers; nonlinear control systems; pendulums; position control; self-adjusting systems; stability; three-term control; tuning; double inverted pendulum; gain parameters; self-tuning neuro-PID; stabilization; Computer architecture; Control systems; Intelligent control; Neural networks; Neurons; PD control; Pi control; Proportional control; Three-term control; Tuning;
Conference_Titel :
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location :
Como
Print_ISBN :
0-7695-0619-4
DOI :
10.1109/IJCNN.2000.860795
