Title :
PID-like neural network nonlinear adaptive control
Author :
Liang Yan-yang ; Cong Shuang ; Liu Hong-wei
Author_Institution :
Dept. of Inf. Eng., Southwest Univ. of Sci. & Technol., Mianyang, China
Abstract :
A PID-like neural network nonlinear adaptive controller is proposed with the combination of neural network principle and PID controller. The adaptive update law of PID parameters is obtained by resilient back-propagation algorithm with sign, and then the value of learning rate is derived applying discrete Lyapunov direct method to insure control system stability. Finally, based on the simulation software system constructed by MATLAB and ADAMS, the proposed controller is applied to the stabilizing control of triple inverted pendulum.
Keywords :
Lyapunov methods; adaptive control; backpropagation; neurocontrollers; nonlinear control systems; pendulums; stability; three-term control; ADAMS software; Lyapunov direct method; Matlab software; PID-like neural network; adaptive control; adaptive update law; control system stability; learning rate; nonlinear control; resilient backpropagation algorithm; triple inverted pendulum; Adaptation model; Adaptive control; Artificial neural networks; Electronic mail; MATLAB; Tuning; Adaptive Control; Neural Network; PID; Triple Inverted Pendulum; Virtual Prototyping Technology;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
