Title :
Single neuron ADRC control based on RBF neural network on-line identification
Author :
Su Si-Xian ; Yang Hui-zhong
Author_Institution :
Key Lab. of Adv. Process Control for Light Ind., Jiangnan Univ., Wuxi, China
Abstract :
Arming at the problem of over many parameters to be turned in the active disturbance rejection controller (ADRC), a self-adaptive single neuron Active Disturbance Rejection Control (ADRC) is proposed based on RBF neural network on-line identification, which identifies the Jacobian matrix of controlled object by means of RBF neural network identifier and acquires on-line tuning information of ADRC parameters. The self-tuning of the controller parameters is implemented by the single neuron controller, and the intelligent control of the system is achieved. The simulation result indicates that the proposed control system greatly reduces the adjusted parameter and possesses the advantages of high precision, great adaptability and robustness.
Keywords :
Jacobian matrices; adaptive control; intelligent control; neurocontrollers; radial basis function networks; Jacobian matrix; RBF neural network online identification; active disturbance rejection controller; intelligent control; single neuron ADRC control; Biological neural networks; Electronic mail; Jacobian matrices; Neurons; Object recognition; Robustness; Sensitivity analysis; Active Disturbance Rejection Control (ADRC); Nonlinear state error feedback; RBF neural network; Single neuron;
Conference_Titel :
Control Conference (CCC), 2011 30th Chinese
Conference_Location :
Yantai
Print_ISBN :
978-1-4577-0677-6
Electronic_ISBN :
1934-1768