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Controlling of pneumatic muscle actuator systems by Parallel Structure of Neural Network and Proportional Controllers (PNNP)

Al-Ibadi, A; Nefti-Meziani, S; Davis, ST

Authors

A Al-Ibadi

S Nefti-Meziani

ST Davis



Abstract

This article proposed a novel controller structure to track the nonlinear behavior of the pneumatic muscle actuator (PMA), such as the elongation for the extensor actuator and bending for the bending PMA. The proposed controller consists neural network (NN) controller laid in parallel with the proportional controller (P). The parallel neural network-proportional (PNNP) controllers provide a high level of precision and fast-tracking control system. The PNNP has been applied to control the length of the single extensor PMA and the bending angle of the single self-bending contraction actuator (SBCA) at different load values. For further validation, the PNNP applied to control a human-robot shared control system. The results show the efficiency of the proposed controller structure.

Citation

Al-Ibadi, A., Nefti-Meziani, S., & Davis, S. (2020). Controlling of pneumatic muscle actuator systems by Parallel Structure of Neural Network and Proportional Controllers (PNNP). Frontiers in Robotics and AI, 7, 115. https://doi.org/10.3389/frobt.2020.00115

Journal Article Type Article
Acceptance Date Jul 22, 2020
Online Publication Date Oct 5, 2020
Publication Date Oct 5, 2020
Deposit Date Jul 28, 2020
Publicly Available Date Oct 6, 2020
Journal Frontiers in Robotics and AI, section Soft Robotics
Publisher Frontiers Media
Volume 7
Pages 115
DOI https://doi.org/10.3389/frobt.2020.00115
Publisher URL https://doi.org/10.3389/frobt.2020.00115
Related Public URLs http://www.frontiersin.org/Robotics_and_AI

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