Title :
Robust PID sliding mode control of robot manipulators with online learning neural network
Author :
Pham Thuong Cat ; Nguyen Tran Hiep
Author_Institution :
Inst. of Inf. Technol., Hanoi, Vietnam
Abstract :
The paper presents a new adaptive control algorithm for robot motion tracking problem to overcome noises and large uncertainties using integral sliding surface with a neural network. The control quality has been improved compared to conventional PD type sliding surface. It removes chattering and increases the accuracy. The weights of the neural network are updated continuously online granting the approximation of uncertain nonlinearities in the robot dynamics. The stability of the overall system has been proved by Lyapunov direct method. Computer simulations are given to illustrate the robustness and applicability of the proposed method.
Keywords :
Lyapunov methods; adaptive control; control nonlinearities; learning (artificial intelligence); manipulator dynamics; motion control; neurocontrollers; radial basis function networks; robust control; variable structure systems; Lyapunov direct method; RFB neural network; adaptive control algorithm; computer simulation; control quality; integral sliding surface; online learning neural network; robot dynamics; robot manipulators; robot motion tracking problem; robust PID sliding mode control; robustness; system stability; uncertain nonlinearities; Decision support systems; Europe; Manipulators; Neural networks; Robustness; Sliding mode control;
Conference_Titel :
Control Conference (ECC), 2009 European
Conference_Location :
Budapest
Print_ISBN :
978-3-9524173-9-3
