|Stability Analysis of Reference Compensation Technique for Controlling Robot Manipulators by Neural Network
International Journal of Control, Automation, and Systems, vol. 15, no. 2, pp.952-958, 2017
Abstract : "Neural network control for robot manipulators is aimed to compensate for uncertainties in the robot
dynamics. The location of a compensating point differentiates the control scheme into two categories, the feedback
error learning (FEL) scheme and the reference compensation technique (RCT). The RCT scheme is relatively less
used although it has several structural advantages. In this paper, the global stability of the RCT scheme is analyzed
on the basis of Lyapunov function. The analysis turns out that the stability depends upon the magnitude of the
controller gains. Simulation studies of controlling the position of a two-link robot manipulator are conducted."
Neural network control, RCT scheme, robot manipulators, stability.
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