Title :
Self-tuning neuro-PID for SIMO systems
Author :
Omatu, S. ; Fujinaka, T. ; Kishida, Y. ; Yoshioka, M.
Author_Institution :
Dept. of Comput. & Syst. Sci., Osaka Prefecture Univ., Sakai, Japan
fDate :
Aug. 31 1999-Sept. 3 1999
Abstract :
This paper is concerned with a new architecture of a self-tuning neuro-PID control system and its application to stabilization of an inverted pendulum. A single-input multi-output system is considered to control the inverted pendulum by using the PID controller. The PID gains are tuned by using two kinds of neural networks. The simulation results show effectiveness of the proposed approach.
Keywords :
adaptive control; neurocontrollers; nonlinear control systems; pendulums; self-adjusting systems; stability; three-term control; PID gain tuning; SIMO systems; inverted pendulum stabilization; neural networks; self-tuning neuro-PID control system; single-input multioutput system; Biological neural networks; Jacobian matrices; Neurons; PD control; Tuning; Inverted pendulum; Neural networks; SIMO; Self-tuning PID;
Conference_Titel :
Control Conference (ECC), 1999 European
Conference_Location :
Karlsruhe
Print_ISBN :
978-3-9524173-5-5
