Robust PID sliding mode control of robot manipulators with online learning neural network

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 inc...

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Bibliographic Details
Main Authors: Cat, Pham Thuong, Hiep, Nguyen Tran
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Computer simulation
Decision support systems
Dynamical systems
Europe
Manipulators
Neural networks
Robot control
Robots
Robustness
Sliding
Sliding mode control
Vibration
Online Access:Request full text
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Summary: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.
DOI:10.23919/ECC.2009.7074729