Title :
Adaptive PID Neuro-Controller for a Nonlinear Servomechanism
Author :
Dhaouadi, Rached ; Jafari, Reza
Author_Institution :
American Univ. of Sharjah, Sharjah
Abstract :
In this paper we propose an adaptive PID control scheme based on recurrent neural networks (RNN). The control system includes a RNN-PID control network and a RNN emulator. The recurrent neural networks are trained on-line using the RTRL learning algorithm. The plant sensitivity Information is calculated on-line using the emulator network and is fed back along with other inputs to train the control network. On-line simulation studies and results for a one-degree of freedom robot arm servomechanism are presented to show the effectiveness of the proposed control scheme.
Keywords :
learning (artificial intelligence); manipulators; neurocontrollers; nonlinear control systems; servomechanisms; three-term control; RTRL learning algorithm; adaptive PID neuro-controller; emulator network; nonlinear servomechanism; recurrent neural networks; robot arm servomechanism; Adaptive control; Adaptive systems; Control systems; Neural networks; Programmable control; Recurrent neural networks; Robust control; Servomechanisms; Sliding mode control; Three-term control; Adaptive PID; Emulator; Nonlinear system; Recurrent neural network; Reference model; Servomechanism;
Conference_Titel :
Industrial Electronics, 2007. ISIE 2007. IEEE International Symposium on
Conference_Location :
Vigo
Print_ISBN :
978-1-4244-0754-5
Electronic_ISBN :
978-1-4244-0755-2
DOI :
10.1109/ISIE.2007.4374591