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Robust control of a silicone soft robot using neural networks
Gang Zheng, Yuan Zhou, Mingda Ju

Robust control of a silicone soft robot using neural networks

Author / Organization:
Science & Mathematics Published 2020 Verification Pending

Overview & Synopsis

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.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Robust control of a silicone soft robot using neural networks
Author / Organization Gang Zheng, Yuan Zhou, Mingda Ju
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2020
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-226396
Original Source Link Visit Source Page on hal.science »