基于神经网络的气动人工肌肉机器人手臂智能扭转滑模控制器

S. Boudoua, M. Hamerlain, F. Hamerlain
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引用次数: 8

摘要

本文提出了一种基于神经网络的智能扭转滑模控制器,实现了气动人工肌肉机械臂的颤振控制。该系统是高度非线性的,在某种程度上难以建模,因此需要采用鲁棒控制。由于其作为通用逼近器的性质,在本工作中,使用具有在线自适应学习律的两层神经网络来重建未知和未建模的机器人动力学,并通过设计非线性滑动面来实现两层滑模。用李雅普诺夫方法保证了整个系统的稳定性。给出了实验结果并进行了讨论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent twisting sliding mode controller using neural network for pneumatic artificial muscles robot arm
In this note we present a novel intelligent twisting sliding mode controller using neural network, achieving chatter reduction for the control of pneumatic artificial muscles robot arm. The system is highly non-linear and somehow difficult to model therefore resorting to robust control is required. Thanks to their property as universal approximators, in this work a two layer NN with on line adaptive learning law is used to reconstruct unknown and unmodeled robot dynamics, and the realisation of a two sliding mode is achieved through the design of a nonlinear sliding surface. The stability of the overall system is guaranteed by lyapunov method. Experimental results are presented and discussed.
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