Title :
Inverted Pendulum RBF Neural Network PID Controller Design
Author :
Yu Jing ; Fang Jian
Author_Institution :
Inst. of Electr. Eng., Jilin Teachers´ Inst. of Eng. & Technol., Changchun, China
Abstract :
In view of the first-order inverted pendulum problem such as poor stability, large amount of overshoot, using RBF neural network to PID parameters self-tuning control system. This paper analyzes the RBF neural network tuning PID principles, and for an inverted pendulum system simulation. Simulation results show that the use of RBF neural network tuning PID controller adaptive ability, good quickness, good quality control.
Keywords :
control system synthesis; neurocontrollers; nonlinear control systems; pendulums; radial basis function networks; self-adjusting systems; three-term control; PID parameters self-tuning control system; RBF neural network PID controller design; RBF neural network tuning; first-order inverted pendulum problem; inverted pendulum system simulation; Biological neural networks; Mathematical model; PD control; Radial basis function networks; Tuning; Inverted pendulum; Neural network;
Conference_Titel :
Computer, Consumer and Control (IS3C), 2014 International Symposium on
Conference_Location :
Taichung
DOI :
10.1109/IS3C.2014.152