Robust control of a silicone soft robot using neural networks.

Clicks: 242
ID: 72286
2019
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Abstract
This paper deals with the robust controller design problem to regulate the position of a soft robot with elastic behavior, driven by 4 cable actuators. In this work, we first used an artificial neural network to approximate the relation between these actuators and the controlled position of the soft robot, based on which two types of robust controllers (type of integral and sliding mode) are proposed. The effectiveness and the robustness of the proposed controllers have been analyzed both for the constant and the time-varying disturbances. The performances (precision, convergence speed and robustness) of the proposed method have been validated via different experimental tests.
Reference Key
zheng2019robustisa Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Zheng, Gang;Zhou, Yuan;Ju, Mingda;
Journal ISA transactions
Year 2019
DOI
S0019-0578(19)30559-2
URL
Keywords
Machine learning robust control soft robot

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