Neural network adaptive command filtered control of robotic manipulators with input saturation. (13th December 2019)

• Record Type: Journal Article
• Authors: Wang, Lin; Yang, Chunzhi
• Is Part Of: International journal of advanced robotic systems. Volume 16:Number 6(2019:Nov./Dec.)
• Publication Date: 2019-12-13
• Subjects: Adaptive neural network control -- robotic manipulator -- finite-time stability -- command filtered control; Robotics -- Periodicals; Robotics; Periodicals; 629.892
• DOI: 10.1177/1729881419894779
• Languages: English
• ISSNs: 1729-8806

Abstract

This paper investigates finite-time control of uncertain robotic manipulators with external disturbances by means of neural network control and backstepping technique. To solve the "explosion of terms" in traditional backstepping control, a second-order command filter is designed, and the virtual input and its first-order derivative can be obtained accurately in a finite time. The parameters of the neural network are updated by using the tracking error signals. The proposed controller can guarantee that the tracking error converges to a small region of the origin in some finite time. Finally, we give a simulation study to show the effectiveness of the proposed method.