Sliding mode variable structure control based on neural networks compensation for robotic manipulators

Abstract

Abstract: In this paper, fast terminal sliding mode controller with a neural network based compensator is developed for robotic manipulators with modelling uncertainties and disturbs. The two-power terminal sliding mode approach can make the system states fast converge to zero in a finite time. The neural network for compensating the uncertainties is trained on line based on Lyapunov theory and thus its convergence is guaranteed. Chattering is reduced and even eliminated. Simulation results verify the validity of the control scheme.

Key words: fast terminal sliding mode, neural network, robot, chattering

摘要： 针对机器人控制系统中存在的建模误差和不确定性干扰，提出了基于神经网络补偿的滑模变结构控制。该方法采用双幂次快速终端滑模控制使得系统能在有限时间内快速达到滑模面和平衡点，采用径向基函数神经网络自适应地补偿建模误差和不确定干扰，并通过李雅普诺夫直接法设计权值更新率，确保了系统的全局稳定性，有效抑制了抖震。对两关节机器人的仿真结果表明了该方法的有效性。

关键词: 快速终端滑模, 神经网络, 机器人, 抖震

LI Wenbo, WANG Yaonan. Sliding mode variable structure control based on neural networks compensation for robotic manipulators[J]. Computer Engineering and Applications, 2014, 50(23): 251-255.

李文波，王耀南. 基于神经网络补偿的机器人滑模变结构控制[J]. 计算机工程与应用, 2014, 50(23): 251-255.

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Sliding mode variable structure control based on neural networks compensation for robotic manipulators

基于神经网络补偿的机器人滑模变结构控制

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