|Improvement of Tracking Control of a Sliding Mode Controller for Robot Manipulators by a Neural Network
International Journal of Control, Automation, and Systems, vol. 16, no. 2, pp.937-943, 2018
Abstract : "This article presents a neural network control technique to improve the tracking performance of a robot
manipulator controlled by the sliding mode control method in a non-model-based framework. The sliding mode
controller is a typical nonlinear controller that has been well developed in theory and used in many applications due
to its simplicity and practicality. Selection of the gain of the nonlinear function plays an important role in performance
as well as stability. When the sliding mode controller is used for the non model-based configuration in robot
control, the nonlinear gain should be selected large enough to guarantee the stability. Since the appropriate selection
of the gain value is essential and difficult in the sliding mode control framework, a neural network compensator is
introduced at the trajectory level to help the fixed gain deal with the stability and performance more intelligently.
Stability of the proposed control scheme is analyzed. Simulation studies of following the Cartesian trajectory for a
three-link rotary robot manipulator are conducted to confirm the control improvement by the neural network."
Neural network, reference compensation technique, robot manipulators, sliding mode control.
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