Neural network based control scheme for redundant robot manipulators subject to multiple self-motion criteria

• Published in: Mathematical and computer modelling Vol. 55; no. 3; pp. 1275 - 1300
• Main Authors: Singh, H.P., Sukavanam, N.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2012
• Subjects: computer techniques; decision making; Feed-forward neural network; Lyapunov stability; monitoring; Multiple self-motion criteria; neural networks; Redundant manipulator; Uncertainties; Lyapunov stability; Feed-forward neural network; Uncertainties; Multiple self-motion criteria; Redundant manipulator
• ISSN: 0895-7177; 1872-9479
• DOI: 10.1016/j.mcm.2011.10.007

The aim of this paper is to design a neural network based adaptive control scheme for redundant manipulators in the presence of model uncertainties and external disturbances together with multiple self-motion criteria. With reference to the paper (N. Kumar, V. Panwar, N. Sukavanam, S.P. Sharma, J.H. Borm, Neural network based nonlinear tracking control of kinematically redundant robot manipulators, Mathematical and Computer Modelling 53 (2011) 1889–1901), an adaptive mechanism is also developed to estimate the uncertain bound of external disturbances and neural network approximation error etc. without requirement of known bounds. By Lyapunov method asymptotic error convergence can be guaranteed for both task-space and sub-task tracking errors. A comparative simulation study with a robust controller and the proposed controller are included for a 3 link planar robot manipulator.