Title :
Inverted Pendulum System Control by Using Modified PID Neural Network
Author :
Li, Shouju ; Huo, Chenfang ; Liu, Yingxi
Author_Institution :
State Key Lab. of Struct. Anal. for Ind. Equip., Dalian Univ. of Technol., Dalian
Abstract :
An improved PID neural network-based controller is designed and analyzed for the inverted pendulum system. In order to deal with the local minimum problem in training neural network with backpropagation algorithm and to enhance controlling precision, neural network´s weights are adjusted by optimization algorithm. The controller employs a PID neural network instead of estimating the unknown plant nonlinearities on-line. The simulation results show that the proposed controller with improved PID neural network is flexible and efficient in the control of inverted pendulum system.
Keywords :
control nonlinearities; control system synthesis; neurocontrollers; nonlinear control systems; optimisation; pendulums; three-term control; backpropagation algorithm; controller design; inverted pendulum system control; local minimum problem; modified PID neural network; optimization algorithm; unknown plant nonlinearities; Artificial neural networks; Backpropagation algorithms; Control systems; Neural networks; Neurons; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; Signal processing algorithms; Three-term control;
Conference_Titel :
Innovative Computing Information and Control, 2008. ICICIC '08. 3rd International Conference on
Conference_Location :
Dalian, Liaoning
Print_ISBN :
978-0-7695-3161-8
Electronic_ISBN :
978-0-7695-3161-8
DOI :
10.1109/ICICIC.2008.333