DocumentCode
3548775
Title
Robust Composite Saturation Compensation for a Single Flexible Link Using Neural Networks
Author
Gao, Wenzhi ; Selmic, Rastko R. ; Lewis, Frank L.
Author_Institution
Dept. of Electr. Eng., Louisiana Tech. Univ., Ruston, LA
fYear
2005
fDate
27-29 June 2005
Firstpage
280
Lastpage
285
Abstract
A robust neural network (NN) composite saturation compensation scheme is presented for a trajectory tracking and a vibration suppression of a flexible link robot arm. The scheme is based on a singular-perturbation technique and can accommodate an unknown disturbance and the saturation constraints. The saturation compensator is composed of a robust fast sub-compensator for stabilization of the fast, flexible modes and a slow sub-compensator for a stable tracking control of the slow, rigid modes. The actuator saturation is assumed unknown. A NN-based slow subcompensator is inserted into the feedforward path. The stability analysis is based on the Lyapunov theory. Simulation results indicate that the proposed scheme can effectively compensate the saturation nonlinearity for underactuated systems
Keywords
Lyapunov methods; compensation; feedforward; flexible manipulators; neurocontrollers; position control; robust control; vibration control; Lyapunov theory; actuator saturation; feedforward path; neural networks; robot arm; robust composite saturation compensation; single flexible link; singular-perturbation technique; stability analysis; trajectory tracking; underactuated systems; vibration suppression; Friction; Gravity; Intelligent actuators; Intelligent control; Lagrangian functions; Manipulator dynamics; Matrix decomposition; Neural networks; Robot kinematics; Robustness;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation
Conference_Location
Limassol
ISSN
2158-9860
Print_ISBN
0-7803-8936-0
Type
conf
DOI
10.1109/.2005.1467028
Filename
1467028
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